Coffee and tea consumption and the risk of head and neck cancer: An updated pooled analysis in the International Head and Neck Cancer Epidemiology Consortium

Abstract

Key Aspects

• Study Objective: The primary objective of this study is to investigate the relationship between coffee and tea consumption and the incidence of head and neck cancer (HNC). This is driven by the increasing global burden of HNC and the unclear nature of the association between these commonly consumed beverages and HNC risk.
• Methodology: The study employs a pooled analysis methodology, combining data from 14 individual-level case-control studies within the International Head and Neck Cancer Epidemiology (INHANCE) consortium. This approach involves 9548 HNC cases and 15,783 controls. The researchers used random-effects logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for various sociodemographic and lifestyle factors to minimize confounding.
• Key Findings: Coffee Consumption: The study found that consuming more than 4 cups of caffeinated coffee daily was inversely associated with the risk of HNC overall, as well as specifically with oral cavity and oropharyngeal cancers. Consuming 3-4 cups of caffeinated coffee daily was inversely associated with hypopharyngeal cancer. Drinking decaffeinated coffee and consuming between >0 to <1 cup of caffeinated coffee daily were inversely associated with oral cavity cancer.
• Key Findings: Tea Consumption: Drinking tea was found to be inversely associated with the risk of hypopharyngeal cancer. Daily tea consumption of >0 to ≤1 cup was inversely associated with HNC overall and hypopharyngeal cancer. However, drinking more than 1 cup of tea daily was associated with an increased risk of laryngeal cancer.
• Conclusions: The study concludes that the findings support a reduced risk of HNC among coffee and tea drinkers, although the association varies by HNC subsite and type of beverage. The authors highlight the need for future research to address geographical differences in coffee and tea types and to improve the understanding of the association between these beverages and global HNC risk.

Strengths

• Large Sample Size and Pooled Analysis

  The study utilizes a large dataset from the INHANCE consortium, enhancing statistical power and generalizability.

  "A pooled analysis of 9548 HNC cases and 15,783 controls from 14 individual‐level case‐control studies" (Page 1)
• Comprehensive Adjustment for Confounders

  The analysis adjusts for a wide range of sociodemographic and lifestyle factors, increasing the validity of the findings.

  "adjusting for sociodemographic and lifestyle factors." (Page 1)
• Detailed Subsite Analysis

  The study examines associations for specific HNC subsites, providing a more nuanced understanding of the relationship.

  "ORs) and 95% confidence intervals (CIs) for HNC and its subsites" (Page 1)

Suggestions for Improvement

• Clarify Dose-Response Relationship

  This medium-impact improvement would enhance the clarity and interpretability of the findings. The Abstract section is the first point of contact for many readers, and a clear presentation of the dose-response relationship is crucial for understanding the main results. Explicitly stating the presence or absence of a dose-response relationship would strengthen the paper by providing a more complete picture of the association between coffee/tea consumption and HNC risk. This would also aid readers in quickly grasping the key takeaways of the study. Ultimately, providing a concise summary of the dose-response relationship would improve the Abstract's informativeness and enhance the reader's understanding of the study's findings.

  "Compared to non–coffee drinkers, drinking >4 cups of caffeinated coffee daily was inversely associated with HNC" (Page 1)

  Implementation: Add a sentence summarizing the observed dose-response relationship for both coffee and tea consumption. For example: "A dose-response relationship was observed for coffee consumption, with increasing intake associated with a greater reduction in HNC risk. For tea, a dose-response relationship was observed for overall HNC and hypopharyngeal cancer, but an increased risk was found for laryngeal cancer with higher consumption."

• Specify Coffee and Tea Types

  This medium-impact improvement would enhance the study's precision and relevance. As the Abstract introduces the study's scope, clarifying the types of coffee and tea investigated is important for accurate interpretation of the findings. Specifying the types of coffee (e.g., caffeinated, decaffeinated) and tea (e.g., black, green) would strengthen the paper by providing context for the observed associations and allowing for comparisons with other studies. This would also help readers understand the potential mechanisms involved. In conclusion, defining the types of coffee and tea studied would improve the Abstract's specificity and contribute to a more precise understanding of the study's findings.

  "The relations between coffee and tea consumption and head and neck cancer (HNC) incidence are unclear." (Page 1)

  Implementation: Briefly mention the types of coffee and tea included in the analysis. For example: "This study examined the association between caffeinated and decaffeinated coffee, as well as black and green tea, and HNC risk."

• Provide Context for Inverse Association with Laryngeal Cancer

  This high-impact improvement would significantly improve the clarity and interpretation of a seemingly contradictory finding. The Abstract is crucial for conveying the study's main results, and providing context for this finding is essential for a balanced understanding. Adding a brief explanation for the positive association between tea consumption and laryngeal cancer would strengthen the paper by addressing a potential source of confusion for readers. This would also demonstrate the authors' awareness of the complexity of the relationship and their consideration of potential mechanisms. In summary, providing context for the laryngeal cancer finding would greatly enhance the Abstract's clarity and ensure a more nuanced understanding of the study's results.

  "Drinking tea was inversely associated with hypopharyngeal cancer (OR, 0.71; 95% CI, 0.59–0.87)." (Page 1)

  Implementation: Add a brief phrase or sentence explaining the potential mechanism behind the increased risk of laryngeal cancer with higher tea consumption. For example: "While tea consumption was generally associated with reduced HNC risk, an increased risk of laryngeal cancer was observed with higher intake, potentially due to the mediation of gastroesophageal reflux disease (GERD)."

Introduction

Key Aspects

• Global Burden of Head and Neck Cancer: Head and neck cancer (HNC) represents a significant global health concern, ranking as the seventh most common cancer worldwide. In 2020, approximately 745,000 new cases and 364,000 deaths were attributed to HNC. While the overall incidence is declining in high-income countries, the incidence of oropharyngeal cancer is rising due to increasing human papillomavirus infections. Low- and middle-income countries bear a disproportionate burden, accounting for two-thirds of global HNC cases, largely due to limited public health resources.
• Need for Primary Prevention: Despite improvements in 5-year survival rates, the increasing incidence of oropharyngeal cancer in high-income countries and the overall HNC burden in low- and middle-income countries highlight the critical need to understand HNC risk factors. This understanding is essential for developing effective primary prevention strategies to reduce the global incidence of HNC.
• Role of Dietary Factors: Coffee and Tea: While tobacco and alcohol are well-established risk factors for HNC, the influence of dietary factors, particularly coffee and tea consumption, remains unclear. Coffee and tea are globally popular beverages containing bioactive compounds with potential antioxidant, anticancer, and anti-inflammatory properties. These compounds include caffeine, polyphenols, trigonelline, chlorogenic acids, cafestol, and kahweol in coffee, and caffeine, polyphenols, catechins, flavanols, lignans, and phenolic acid in tea.
• Inconsistent Findings on Coffee and HNC Risk: Epidemiological studies investigating the association between coffee consumption and HNC risk have yielded inconsistent results. Some studies have reported inverse associations between coffee consumption and the risk of oral cavity and pharyngeal cancers, while others have found no association or even an increased risk for specific HNC subsites, such as laryngeal cancer.
• Inconsistent Findings on Tea and HNC Risk: Similar to coffee, studies examining the relationship between tea consumption and HNC risk have also produced inconsistent findings. Some studies suggest a protective effect of tea, particularly green tea, against oral cancer, while others, including a previous analysis from the International Head and Neck Cancer Epidemiology (INHANCE) consortium, have found no significant association between tea drinking and HNC risk.
• Previous INHANCE Study and Current Study Objective: A previous pooled analysis within the INHANCE consortium reported an inverse association between caffeinated coffee and oral cavity and pharyngeal cancers but found no association for decaffeinated coffee or tea. The current study aims to further investigate the relationship between coffee and tea consumption and HNC risk using an updated and larger dataset from the INHANCE consortium.

Strengths

• Clear Problem Statement

  The Introduction effectively establishes the significance of HNC as a global health problem and highlights the need for further research into its risk factors.

  "Head and neck cancer (HNC)...is the seventh most common cancer worldwide" (Page 2)
• Comprehensive Background on Coffee and Tea

  The section provides a thorough overview of the existing literature on coffee and tea consumption and HNC risk, acknowledging the inconsistencies in previous findings.

  "Although tobacco and alcohol are established HNC risk factors, the role of dietary factors including coffee and tea consumption have not yet been fully understood." (Page 2)
• Justification for Updated Analysis

  The Introduction clearly justifies the need for an updated analysis using a larger dataset from the INHANCE consortium to address the limitations of previous studies.

  "To better understand the relationship between coffee and tea consumption and the risk of HNC, we assessed the associations using an updated larger set of cases" (Page 2)

Suggestions for Improvement

• Strengthen Rationale for Focus on Coffee and Tea

  This medium-impact improvement would further solidify the study's rationale. While the Introduction mentions the popularity and potential health effects of coffee and tea, explicitly linking these factors to the need for further investigation in the context of HNC would strengthen the justification for this specific research focus. Elaborating on the potential mechanisms by which coffee and tea might influence HNC risk, based on their bioactive compounds, would enhance the scientific foundation of the study. This would also provide a stronger connection between the background information and the research question. Ultimately, strengthening the rationale for focusing on coffee and tea would enhance the Introduction's persuasiveness and highlight the study's potential contribution to understanding HNC prevention.

  "Coffee and tea are two popular beverages consumed worldwide, containing bioactive compounds with potential antioxidant, anticancer, and anti-inflammatory effects." (Page 2)

  Implementation: Add a paragraph that elaborates on why coffee and tea are particularly relevant to study in the context of HNC. For example: "Given their widespread consumption and the presence of bioactive compounds with potential anticancer properties, coffee and tea represent promising candidates for investigating dietary factors that may modify HNC risk. Understanding the association between these beverages and HNC could inform public health recommendations and contribute to primary prevention strategies."

• Elaborate on INHANCE Consortium

  This low-impact improvement would provide valuable context for readers unfamiliar with the INHANCE consortium. Briefly describing its scope and significance in the field of HNC epidemiology would enhance the Introduction's informativeness. Providing a concise overview of the INHANCE consortium would strengthen the paper by highlighting the robust nature of the dataset being used. This would also help readers understand the collaborative and international effort behind this research. In conclusion, adding a brief description of the INHANCE consortium would improve the Introduction's clarity and provide important context for the study's methodology.

  "International Head and Neck Cancer Epidemiology consortium (INHANCE)" (Page 2)

  Implementation: Add a sentence or two describing the INHANCE consortium. For example: "The International Head and Neck Cancer Epidemiology (INHANCE) consortium is a large-scale international collaboration that pools data from multiple case-control studies to investigate the risk factors for HNC. This collaborative effort provides a robust platform for examining the association between various exposures, including coffee and tea consumption, and HNC risk."

• Clarify Study Objective

  This high-impact improvement would significantly enhance the Introduction's clarity and focus. While the section mentions the aim to assess associations using an updated dataset, explicitly stating the primary objective as investigating the relationship between coffee and tea consumption and HNC risk would provide a more precise and impactful introduction to the study. Clearly stating the study objective would strengthen the paper by immediately orienting the reader to the central research question. This would also establish a clear link between the background information and the study's purpose. In summary, explicitly stating the study objective would greatly enhance the Introduction's clarity and provide a strong foundation for the rest of the paper.

  "To better understand the relationship between coffee and tea con- sumption and the risk of HNC, we assessed the associations using an updated larger set of cases" (Page 2)

  Implementation: Add a clear statement of the study objective at the end of the Introduction. For example: "Therefore, the primary objective of this study is to investigate the association between coffee and tea consumption and the risk of head and neck cancer using an updated and expanded dataset from the INHANCE consortium."

Materials and Methods

Key Aspects

• Data Source and Study Population: This study utilizes pooled data from the International Head and Neck Cancer Epidemiology (INHANCE) consortium. The INHANCE consortium is a large-scale collaborative effort that combines data from multiple case-control studies worldwide to investigate risk factors for head and neck cancer (HNC). This particular analysis includes data from 14 case-control studies, encompassing 9548 HNC cases and 15,783 controls. These studies collected information on coffee and tea consumption, along with sociodemographic and lifestyle factors such as dietary intake, tobacco use, and alcohol consumption. Participants with missing data for age, sex, and race/ethnicity were excluded.
• Data Collection and Harmonization: Each INHANCE study employed study-specific questionnaires to gather data, including detailed information on coffee and tea consumption. Participants were asked to recall their prior consumption of caffeinated coffee, decaffeinated coffee, and tea in cups per day, week, month, or year. While most studies used recall questions, two studies (Boston and Seattle) used food frequency questionnaires. Efforts were made to standardize data across studies. For instance, caffeinated coffee consumption was categorized into nondrinkers, >0 to <3 cups, 3-4 cups, and >4 cups per day. Decaffeinated coffee was categorized as nondrinker, >0 to <1 cup, and ≥1 cups per day. Tea consumption was categorized as nondrinker, >0 to ≤1 cup, and >1 cups per day.
• Case and Control Ascertainment: HNC cases included in this analysis were individuals diagnosed with invasive cancers of the oral cavity, oropharynx, hypopharynx, or larynx, as classified by their original study investigators. Cases with cancers of the salivary glands, nasal cavity/ear/paranasal sinuses, and overlapping head and neck subsites were excluded. The International Classification of Diseases for Oncology, version 2 (ICDO-2) was used to classify HNC subsites. Controls were selected from the same source population as their respective cases, and several studies frequency-matched cases and controls on factors such as age, sex, study center, and neighborhood.
• Statistical Analysis: The study employed logistic regression models to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the association between coffee/tea consumption and HNC risk. These models were adjusted for potential confounders, including study center, age, sex, race/ethnicity, education, body mass index (BMI), smoking, alcohol intake, fruit consumption, and vegetable consumption. Missing data were imputed using established methods. A two-stage random-effects logistic regression model with the maximum likelihood method was used to calculate study-specific and pooled estimates. Heterogeneity between studies was assessed using a likelihood ratio test. Stratified analyses and sensitivity analyses were also conducted to assess potential effect modification and the influence of individual studies on the overall results.

Strengths

• Large and Diverse Dataset

  Utilizing the INHANCE consortium data provides a large sample size and diverse population, increasing statistical power and generalizability.

  "The INHANCE pooled data were used in this analysis." (Page 2)
• Detailed Exposure Assessment

  The study collects detailed information on coffee and tea consumption, including type and quantity, allowing for a nuanced analysis.

  "recall their prior consumption of caffeinated coffee, decaffeinated coffee, and tea in cups per day/week/month/year." (Page 2)
• Comprehensive Confounder Adjustment

  The analysis adjusts for a wide range of potential confounders, including demographic, lifestyle, and dietary factors, strengthening the validity of the findings.

  "adjusted for study center, age, sex, race/ethnicity, education level, body mass index (BMI), daily number of cigarettes smoked" (Page 3)
• Rigorous Statistical Methods

  The use of two-stage random-effects logistic regression and heterogeneity testing demonstrates a robust statistical approach.

  "a two-stage random-effects logistic regression model with the maximum likelihood method was used." (Page 3)

Suggestions for Improvement

• Clarify Data Harmonization Procedures

  This high-impact improvement would significantly enhance the transparency and reproducibility of the study. While the Methods section mentions data standardization, providing more specific details about the harmonization process across the 14 different studies is crucial for understanding how comparability was ensured. This is especially important given the potential for variability in data collection methods and definitions across different research centers and time periods. Elaborating on the specific steps taken to harmonize variables, particularly for coffee and tea consumption, would strengthen the paper by allowing readers to better assess the validity of the pooled analysis. This would also facilitate future research efforts aimed at replicating or extending these findings. For example, describing how different categorizations or units of measurement were reconciled would be beneficial. Ultimately, providing a more detailed description of the data harmonization procedures would bolster confidence in the study's findings and contribute to the overall rigor of the research.

  "Caffeinated coffee consumption data was standardized to cups per day" (Page 3)

  Implementation: Add a subsection dedicated to data harmonization, detailing the procedures used to standardize variables across studies. For example: "To ensure comparability across the 14 studies, a rigorous data harmonization process was undertaken. Coffee and tea consumption variables were standardized by converting all measurements to cups per day. For studies that used ranges (e.g., 1-2 cups), the midpoint of the range was used. Where different types of coffee or tea were recorded (e.g., black, green), these were categorized as caffeinated or decaffeinated based on standard definitions. Discrepancies in variable definitions or coding schemes were resolved through consensus discussions among the research team."

• Provide More Detail on Food Frequency Questionnaires

  This medium-impact improvement would enhance the clarity of the exposure assessment methods. As the Methods section notes that two studies used food frequency questionnaires (FFQs), providing more information about these specific FFQs would be beneficial. FFQs can vary in their structure, the food items included, and the time period they cover, which can impact the accuracy and comparability of the data. Describing the key features of the FFQs used in the Boston and Seattle studies would strengthen the paper by providing readers with a better understanding of how coffee and tea consumption were assessed in these studies. This would also allow for a more informed comparison of the results from these studies with those that used recall questions. In conclusion, providing more detail on the FFQs would improve the transparency of the exposure assessment and contribute to a more comprehensive understanding of the study's methodology.

  "the Boston and Seattle studies used food frequency questionnaires to ascertain coffee and tea consumption" (Page 2)

  Implementation: Add a few sentences describing the FFQs used in the Boston and Seattle studies. For example: "The Boston and Seattle studies employed study-specific food frequency questionnaires (FFQs) to assess dietary intake, including coffee and tea consumption. These FFQs inquired about the frequency and portion sizes of various food and beverage items consumed over the past year. The FFQs were validated against dietary records and showed reasonable agreement for coffee and tea consumption."

• Justify Exclusion Criteria

  This low-impact improvement would enhance the transparency of the study population selection. While the Methods section mentions the exclusion of individuals with missing data for age, sex, and race/ethnicity, providing a brief rationale for these specific exclusion criteria would be helpful. Explaining the reasons behind these exclusions would strengthen the paper by providing a clearer understanding of the study population and the potential impact of these exclusions on the results. This would also demonstrate a more thorough consideration of potential biases. In summary, providing a justification for the exclusion criteria would improve the transparency of the study's methodology and enhance the reader's understanding of the study population.

  "Individuals with missing data for age, sex, and race/ethnicity were excluded from this analysis." (Page 2)

  Implementation: Add a sentence or two explaining the rationale for the exclusion criteria. For example: "Individuals with missing data for age, sex, and race/ethnicity were excluded from the analysis because these variables are considered important confounders in the relationship between coffee/tea consumption and HNC risk. Excluding these individuals ensured that the analysis was based on a complete dataset with respect to these key demographic variables."

Statistical analysis

Key Aspects

• Comparison of Cases and Controls: The study compared demographic characteristics and known risk factors for head and neck cancer (HNC) between 9548 cases and 15,783 controls using chi-squared tests or t-tests. Cases were found to have lower education levels, lower body mass index (BMI), higher daily cigarette consumption, and higher daily alcohol consumption compared to controls. Conversely, controls exhibited higher fruit and vegetable intake and shorter durations of cigarette smoking.
• Association between Coffee/Tea Consumption and HNC Risk: Logistic regression models were employed to assess the associations between caffeinated coffee, decaffeinated coffee, and tea consumption and HNC risk. These models estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs), controlling for study center, age, sex, race/ethnicity, education, BMI, smoking (number of cigarettes, duration of cigarette, cigar, and pipe smoking), alcohol intake, fruit consumption, and vegetable consumption. Missing data were imputed using established methods, including those from previous INHANCE studies.
• Calculation of Study-Specific and Pooled Estimates: A two-stage random-effects logistic regression model, utilizing the maximum likelihood method, was used to calculate both study-specific and pooled estimates of the association between coffee/tea consumption and HNC risk. This approach accounts for potential variability between studies. To determine whether to use a random-effects or fixed-effects model, a likelihood ratio test was conducted to assess heterogeneity between studies. This test compared models with and without a product term representing the interaction between study center and coffee/tea consumption for HNC and its subsites. Random-effect estimates were reported when significant heterogeneity (p < 0.05) was detected across study centers; otherwise, fixed-effect estimates were used.
• Stratified and Sensitivity Analyses: To evaluate potential effect modification, a stratified analysis was performed for the consumption of >4 cups of caffeinated coffee daily compared with non-coffee drinkers for oral cavity and oropharyngeal cancers combined. This analysis examined the effect of dichotomized covariates such as age, sex, tobacco consumption, alcohol consumption, fruit intake, vegetable intake, study geographical region, study period, and types of controls. Additionally, a sensitivity analysis was conducted by sequentially excluding each study to ensure that the overall risk estimate's statistical significance and magnitude were not unduly influenced by any single study.
• Software Used: All statistical analyses were performed using either SAS 9.4 (SAS Institute, Cary, North Carolina) or STATA 18.0 (StataCorp LLC., College Station, Texas), two widely used statistical software packages in epidemiological research.

Strengths

• Comprehensive Adjustment for Confounders

  The study meticulously adjusted for a wide array of potential confounders, including demographic factors, lifestyle choices, and dietary habits. This comprehensive adjustment strengthens the validity of the findings by minimizing the influence of extraneous variables on the observed associations.

  "All models were adjusted for study center, age, sex, race/ethnicity, education level, body mass index (BMI), daily number of cigarettes smoked" (Page 3)
• Robust Statistical Methodology

  The use of a two-stage random-effects logistic regression model is appropriate for analyzing pooled data from multiple studies. This method accounts for potential heterogeneity between studies and provides more accurate estimates of the overall effect.

  "a two-stage random-effects logistic regression model with the maximum likelihood method was used." (Page 3)
• Assessment of Heterogeneity

  The study appropriately assessed heterogeneity between studies using a likelihood ratio test. This is important for determining whether a random-effects or fixed-effects model is more suitable for the data.

  "A likelihood ratio test was used to determine heterogeneity between studies" (Page 3)
• Stratified and Sensitivity Analyses

  The inclusion of stratified and sensitivity analyses enhances the robustness of the findings by exploring potential effect modification and assessing the influence of individual studies on the overall results.

  "A stratified analysis for the consumption of >4 cups of caffein- ated coffee daily compared with non-coffee drinkers" (Page 3)

Suggestions for Improvement

• Provide More Detail on Imputation Methods

  This medium-impact improvement would enhance the transparency and reproducibility of the study. While the Methods section mentions the use of imputation for missing data, providing more specific details about the imputation methods employed, particularly for education, fruit, and vegetable consumption, would allow readers to better assess the potential impact of missing data on the results. Elaborating on the specific imputation techniques used, including the variables used in the imputation models and the assumptions made, would strengthen the paper by providing a more complete picture of the data handling procedures. This would also enable other researchers to more accurately replicate the analysis if desired. Ultimately, providing a more detailed description of the imputation methods would increase confidence in the study's findings by addressing potential concerns about the handling of missing data.

  "Missing education data were imputed with methods used in previous INHANCE studies." (Page 3)

  Implementation: Add a subsection or a few sentences detailing the imputation methods. For example: "Missing education data were imputed using a multiple imputation approach, with imputation models including age, sex, study center, and other relevant covariates. For missing fruit and vegetable consumption, a single imputation method was used, imputing the average quartile value for cases and controls separately, based on the observed distribution within each group."

• Justify Choice of Covariates in Regression Models

  This medium-impact improvement would strengthen the rationale behind the statistical analysis. While the Methods section lists the covariates adjusted for in the regression models, providing a brief justification for the inclusion of each covariate would enhance the clarity and rigor of the study. Explaining the reasons for including each covariate, based on prior knowledge or potential confounding effects, would strengthen the paper by demonstrating a thoughtful and informed approach to model building. This would also help readers understand the potential biases that were being addressed through covariate adjustment. In conclusion, providing a justification for the choice of covariates would improve the transparency of the statistical analysis and enhance the reader's understanding of the study's methodology.

  "All models were adjusted for study center, age, sex, race/ethnicity, education level, body mass index (BMI), daily number of cigarettes smoked, duration of cigarette smoking, duration of cigar smoking, duration of pipe smoking, daily number of alcoholic drinks, fruit consumption, and vegetable consumption" (Page 3)

  Implementation: Add a few sentences explaining the rationale for including each covariate. For example: "Covariates were selected based on their potential to confound the association between coffee/tea consumption and HNC risk, as identified in previous studies. Age, sex, and race/ethnicity are known demographic risk factors for HNC. Education level was included as a proxy for socioeconomic status, which may influence both coffee/tea consumption and HNC risk. BMI, smoking, alcohol intake, fruit consumption, and vegetable consumption were included as indicators of lifestyle and dietary factors that may also be associated with HNC."

• Clarify Handling of Continuous Covariates

  This low-impact improvement would enhance the clarity of the statistical methods. While the Methods section mentions that some covariates were continuous (e.g., duration of smoking), it is not entirely clear how these continuous variables were handled in the regression models. Specifying whether they were treated as continuous or categorized would improve the transparency of the analysis. Providing this clarification would strengthen the paper by allowing readers to better understand the specific form of the regression models used. This would also facilitate replication of the analysis by other researchers. In summary, clarifying the handling of continuous covariates would improve the precision and reproducibility of the statistical analysis.

  "duration of cigarette smoking, duration of cigar smoking, duration of pipe smoking, daily number of alcoholic drinks," (Page 3)

  Implementation: Add a sentence or two specifying how continuous covariates were handled. For example: "Continuous covariates, such as duration of cigarette smoking, duration of cigar smoking, and duration of pipe smoking, were included in the regression models as continuous variables. Daily number of cigarettes smoked and daily number of alcoholic drinks were also treated as continuous variables."

Results

Key Aspects

• Study Population Characteristics: The study included 9548 cases of head and neck cancer (HNC) and 15,783 controls. The majority of cases were non-Hispanic White (92.9%) and male (79.3%). Compared to controls, cases had lower education levels, lower body mass index (BMI), higher daily cigarette consumption, and higher daily alcoholic drink consumption. Controls had higher fruit and vegetable intake and shorter duration of cigarette smoking.
• Caffeinated Coffee and HNC Risk: Caffeinated coffee drinking status was not associated with the overall risk of HNC or its subsites when comparing drinkers to non-coffee drinkers. However, consuming more than 4 cups of caffeinated coffee daily was associated with a statistically significant decreased risk of HNC overall, oral cavity cancer, and oropharyngeal cancer. Drinking 3-4 cups daily was inversely associated with hypopharyngeal cancer. A dose-response relationship was observed, indicating that increasing levels of daily caffeinated coffee consumption were associated with a reduced risk of HNC, oral cavity, oropharyngeal, hypopharyngeal, and laryngeal cancers, although the p-values for trend were only significant for some subsites.
• Decaffeinated Coffee and HNC Risk: An inverse association was found between decaffeinated coffee consumption and the risk of oral cavity cancer, particularly for those drinking between >0 to <1 cup daily. No significant association was observed between decaffeinated coffee consumption and laryngeal cancer risk.
• Tea Consumption and HNC Risk: Tea drinkers had a reduced risk of hypopharyngeal cancer compared to non-tea drinkers. Daily tea consumption of >0 to ≤1 cup was inversely associated with the risk of overall HNC and hypopharyngeal cancer. However, drinking more than 1 cup of tea daily was associated with an increased risk of laryngeal cancer. A dose-response relationship was observed for daily tea consumption and the risk of HNC, hypopharyngeal, and laryngeal cancers.
• Stratified Analysis for High Caffeinated Coffee Consumption: A stratified analysis was conducted to assess potential effect modification of the association between consuming >4 cups of caffeinated coffee daily and the risk of oral cavity and oropharyngeal cancers combined. The analysis examined various factors, including age, sex, tobacco and alcohol consumption, fruit and vegetable intake, study region, study period, and type of controls. Inverse associations were observed across all strata, suggesting that the protective effect of high caffeinated coffee consumption was consistent across different subgroups.
• Sensitivity Analysis: A sensitivity analysis was performed by removing each study one at a time to evaluate the influence of individual studies on the overall risk estimates. No significant changes in the overall risk estimates were observed, indicating that the findings were robust and not dependent on any single study.

Strengths

• Clear Presentation of Findings

  The Results section clearly presents the findings, organized by type of beverage (caffeinated coffee, decaffeinated coffee, and tea) and HNC subsite. The use of tables further enhances clarity.

  "Caffeinated coffee drinking status was not associated with the risk of HNC, and its subsites compared to non-coffee drinkers" (Page 3)
• Detailed Subsite Analysis

  The study provides a detailed analysis of the association between coffee/tea consumption and various HNC subsites, offering a nuanced understanding of the relationship.

  "However, drinking >4 cups of caffeinated coffee daily was associated with a decreased risk of HNC (OR, 0.83; 95% CI, 0.69- 1.00), oral cavity (OR, 0.70; 95% CI, 0.55-0.89), and oropharyngeal cancers (OR, 0.78; 95% CI, 0.61-0.99)." (Page 3)
• Dose-Response Analysis

  The study examines dose-response relationships, providing valuable information on how the risk of HNC changes with increasing levels of coffee and tea consumption.

  "A dose–response relationship was observed across increasing levels of daily caffeinated coffee drinking for HNC, oral cavity, oropharyngeal, hypopharyngeal, and laryngeal cancers" (Page 3)
• Stratified and Sensitivity Analyses

  The inclusion of stratified and sensitivity analyses strengthens the robustness of the findings by exploring potential effect modification and assessing the influence of individual studies.

  "A stratified analysis for the consumption of >4 cups of caffein- ated coffee daily compared with non–coffee drinkers" (Page 3)

Suggestions for Improvement

• Provide More Context for Null Findings

  This medium-impact improvement would enhance the interpretability of the results. While the Results section reports that caffeinated coffee drinking status was not associated with the risk of HNC overall or its subsites, providing some context for these null findings, especially in light of the positive findings for higher consumption levels, would be beneficial. Adding a brief discussion of potential reasons for the lack of association at lower consumption levels would strengthen the paper by acknowledging the complexity of the relationship and demonstrating a thorough consideration of the findings. This could include mentioning factors such as the potential for a threshold effect or the influence of other lifestyle factors. Ultimately, providing more context for the null findings would improve the Results section's completeness and contribute to a more nuanced understanding of the study's results.

  "Caffeinated coffee drinking status was not associated with the risk of HNC, and its subsites compared to non–coffee drinkers" (Page 3)

  Implementation: Add a sentence or two discussing the null findings for caffeinated coffee drinking status. For example: "While no association was observed between overall caffeinated coffee drinking status and HNC risk, this may be due to the heterogeneity of consumption levels within the 'drinker' category. It is possible that a protective effect only becomes apparent at higher levels of consumption, as suggested by the findings for >4 cups daily."

• Discuss Potential Mechanisms for Laryngeal Cancer Finding

  This high-impact improvement would significantly enhance the Results section's depth and informativeness. While the section reports an increased risk of laryngeal cancer with higher tea consumption, it does not offer any potential explanations for this finding. Briefly discussing potential mechanisms, as is done in the Discussion section, would provide valuable context for interpreting this result. Adding a sentence or two about potential mechanisms, such as the role of gastroesophageal reflux disease (GERD) mediated by theophylline in tea, would strengthen the paper by demonstrating the authors' awareness of the complexity of the relationship and their consideration of potential biological pathways. This would also help readers understand the potential implications of this finding. In conclusion, discussing potential mechanisms for the laryngeal cancer finding in the Results section would greatly enhance its clarity and contribute to a more comprehensive understanding of the study's results.

  "but drinking >1 cup was associated with an increased risk of laryngeal cancer (OR, 1.38; 95% CI, 1.09–1.74)." (Page 4)

  Implementation: Add a sentence or two discussing potential mechanisms for the increased risk of laryngeal cancer with higher tea consumption. For example: "The positive association between tea consumption and laryngeal cancer risk may be related to the potential for theophylline, a compound in tea, to induce gastroesophageal reflux disease (GERD), which has been linked to an increased risk of laryngeal cancer."

• Clarify Statistical Significance in Text

  This low-impact improvement would enhance the clarity and precision of the Results section. While the section reports odds ratios (ORs) and 95% confidence intervals (CIs), it does not always explicitly state whether the findings are statistically significant. Adding this information would improve the accuracy and interpretability of the results. Explicitly stating the statistical significance of the findings would strengthen the paper by allowing readers to quickly assess the strength of the evidence for each association. This would also ensure consistency in the reporting of results. In summary, clarifying the statistical significance of the findings in the text would improve the Results section's clarity and contribute to a more precise understanding of the study's results.

  "However, drinking >4 cups of caffeinated coffee daily was associated with a decreased risk of HNC (OR, 0.83; 95% CI, 0.69– 1.00), oral cavity (OR, 0.70; 95% CI, 0.55–0.89), and oropharyngeal cancers (OR, 0.78; 95% CI, 0.61–0.99)." (Page 3)

  Implementation: When reporting ORs and CIs, explicitly state whether the finding is statistically significant. For example: "Drinking >4 cups of caffeinated coffee daily was significantly associated with a decreased risk of HNC (OR, 0.83; 95% CI, 0.69-1.00; p = 0.05)." or "Drinking 3-4 cups daily was inversely associated with hypopharyngeal cancer (OR, 0.59; 95% CI, 0.39-0.91), which was statistically significant."

Non-Text Elements

TABLE 1 Characteristics of head and neck cancer cases and controls of select...

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TABLE 1 Characteristics of head and neck cancer cases and controls of select INHANCE consortium studies.

Figure/Table Image (Page 4)

First Reference in Text

Of the cases, 92.9% were non-Hispanic White individuals and 79.3% were males (Table 1).

Description

• Purpose of the table: This table summarizes the demographic and lifestyle characteristics of two groups of people: those who have head and neck cancer (called "cases") and those who do not have it (called "controls"). The purpose is to show the differences and similarities between these two groups to help understand what factors might be associated with the development of head and neck cancer. INHANCE consortium here refers to a specific international research group focused on head and neck cancer epidemiology.
• Structure of the table: The table is organized with characteristics listed on the left-hand side, such as age, sex, and smoking habits. Each characteristic is further broken down into categories. For instance, "age" is split into different age ranges. For each category, the table shows the number of individuals and their percentage within the "cases" group and the "controls" group. For instance, under the characteristic "sex", there are categories for "Female" and "Male". If there were 100 people in the "cases" group and 70 were male, it would show "70" as the number and "70%" as the percentage for males in the cases group.
• Types of data presented: The table presents both categorical and continuous data. Categorical data are divided into groups or categories. Examples include "sex" which has categories "Male" and "Female", or "Education level" which might have categories like "No education" and "Less than junior high school". Continuous data, on the other hand, are numerical and represent measurements. For example, "Duration of cigarette smoking (years)" is a continuous variable and is summarized by the mean, which is the average value, and the standard deviation, which is a measure of how spread out the values are around the mean. For instance, if the mean duration of cigarette smoking is 30 years with a standard deviation of 5 years, it means most people in that group smoked for around 25 to 35 years.
• Statistical significance: At the bottom of the table, it is noted that a p-value was calculated for all characteristics using a two-sided chi-squared test. A p-value is a statistical measure that helps determine if the observed differences between the "cases" and "controls" groups are likely due to chance or if they represent a real association. In this context, a p-value less than 0.05 is considered statistically significant. This means that if the p-value for a particular characteristic is less than 0.05, the difference in that characteristic between the two groups is unlikely to be due to random chance and could be a meaningful finding.

Scientific Validity

• Relevance of variables: The variables chosen for inclusion in Table 1, such as age, sex, race/ethnicity, education, BMI, smoking status, alcohol consumption, and fruit/vegetable intake, are well-established risk factors or potential confounders for head and neck cancer. Their inclusion aligns with standard epidemiological practice for investigating cancer etiology.
• Appropriateness of statistical test: The use of the chi-squared test for categorical variables and t-tests for continuous variables is appropriate for comparing characteristics between the case and control groups. The note indicating a significance level of p < .05 is standard for determining statistical significance.
• Data source and pooling: The data is derived from the INHANCE consortium, which combines data from multiple studies. This pooling approach can increase statistical power and generalizability. However, potential heterogeneity between studies should be considered and addressed in the analysis, as is done in the methods section.
• Limitations in the table: The table provides a good overview of the characteristics, but it does not present any measure of association between each characteristic and head and neck cancer risk, like an odds ratio. This is not a limitation as such, because it is not the purpose of the table. It is also unclear whether the characteristics are adjusted for each other, although this is mentioned to be done in the methods section.

Communication

• Clarity of presentation: The table is well-organized and easy to read. The use of bold text for subheadings and the clear labeling of columns and rows enhance readability. The presentation of data as both counts and percentages allows for easy interpretation.
• Use of abbreviations: Abbreviations like BMI and INHANCE are defined in the footnote, which is helpful for readers who may not be familiar with these terms. However, providing a brief definition of the chi-squared test and its purpose would be good, but might be considered too general by the authors.
• Completeness of information: The table provides a comprehensive overview of the demographic and lifestyle characteristics of the study population. However, it might be beneficial to include a brief description of the study population size in the caption or the table itself, although it is mentioned in the text.
• Potential improvements: While the table is generally well-presented, adding a column showing the p-values for each characteristic would make it even more informative. This would allow readers to quickly assess the statistical significance of the differences between the case and control groups for each variable.

TABLE 2 The association with HNC by anatomical subsite for coffee drinking...

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TABLE 2 The association with HNC by anatomical subsite for coffee drinking status and daily coffee consumption among HNC cases and controls from select INHANCE consortium studies.

Figure/Table Image (Page 5)

First Reference in Text

Caffeinated coffee drinking status was not associated with the risk of HNC, and its subsites compared to non-coffee drinkers (Table 2).

Description

• Overall purpose: This table explores whether there's a link between drinking coffee and the risk of getting head and neck cancer (HNC). It looks at this connection in detail by considering different types of coffee (caffeinated and decaffeinated) and different locations of cancer within the head and neck region (e.g., oral cavity, oropharynx).
• Structure and organization: The table is divided into sections based on the type of coffee (caffeinated or decaffeinated) and the specific location of the cancer. For each section, it compares people who drink coffee ("cases") to those who don't drink coffee ("controls"). It then presents the results for different levels of coffee consumption, such as "non-coffee drinker," ">0 to <3 cups," "3-4 cups," and ">4 cups" for caffeinated coffee. It's like sorting people into groups based on how much coffee they drink and then checking if one group has more cancer cases than the others.
• Data presentation and key metrics: For each level of coffee consumption, the table shows the number of controls (people without cancer) and cases (people with cancer). It also provides a number called "OR" (Odds Ratio) along with a range called "95% CI" (95% Confidence Interval). The OR is a measure of association that tells us if drinking coffee is linked to a higher or lower risk of cancer. An OR of 1 means there's no association. An OR greater than 1 suggests an increased risk, while an OR less than 1 suggests a decreased risk. The 95% CI is a range of values that likely contains the true OR. Think of it like a margin of error – the wider the range, the less certain we are about the true OR. For instance, an OR of 0.83 with a 95% CI of 0.69 to 1.00 means we are 95% confident that the true OR is between 0.69 and 1.00.
• Statistical measures: The table also includes "p for heterogeneity" and "p for trend." "P for heterogeneity" helps us understand if the results are consistent across different studies within the INHANCE consortium. A low p-value (less than 0.05) suggests that the results vary significantly between studies. "P for trend" tests if there's a trend between the level of coffee consumption and the risk of cancer. For example, it checks if drinking more cups of coffee is consistently associated with a higher or lower risk. A low p-value (less than 0.05) for the trend test suggests a statistically significant trend.
• Footnotes: The table has extensive footnotes that explain which studies were included in each analysis, the adjustments made in the statistical models, and the abbreviations used. These footnotes provide important details about the methodology and are essential for understanding the nuances of the results. For example, footnote 'a' indicates that the analysis for decaffeinated coffee drinking status included specific studies, while footnote 'b' lists the studies included in the analysis for caffeinated coffee consumption.

Scientific Validity

• Adjustment for confounders: The analysis adjusts for a comprehensive set of potential confounders, including age, sex, study center, race/ethnicity, education, BMI, smoking, alcohol consumption, and fruit and vegetable intake. This adjustment is crucial for isolating the specific effect of coffee consumption on HNC risk.
• Stratification by anatomical subsite: The stratification by anatomical subsite (oral cavity, oropharynx, hypopharynx, larynx) is a strength, as it allows for a more nuanced understanding of the association between coffee consumption and HNC risk. This approach acknowledges that HNC is not a homogeneous disease and that risk factors may vary by subsite.
• Assessment of dose-response relationship: The table examines different levels of coffee consumption, allowing for an assessment of a potential dose-response relationship. The inclusion of the p-value for trend provides a statistical test for this relationship, which is a standard approach in epidemiological studies.
• Heterogeneity testing: The assessment of heterogeneity is important, given that the data are pooled from multiple studies. The use of random-effects models when heterogeneity is present is appropriate.
• Limitations of data presentation: The table is comprehensive, but it might have been helpful to have an overall summary estimate for the effect of any coffee consumption vs. non-coffee consumption, in addition to the subsite-specific analyses. The numerous footnotes, while necessary, make the table somewhat complex to navigate.

Communication

• Clarity of structure: The table is well-structured, with clear headings and subheadings that facilitate navigation. The organization by coffee type and anatomical subsite makes logical sense.
• Use of technical terms: The table uses appropriate technical terms, such as "Odds Ratio" and "Confidence Interval," which are standard in epidemiological reporting. However, some readers might find the extensive use of abbreviations and the detailed statistical information challenging to interpret. The use of superscripts for footnotes is effective but could be overwhelming due to their quantity.
• Complexity of information: The table presents a large amount of information, which can be difficult to digest at a glance. The detailed breakdown by subsite and consumption level is valuable but adds to the complexity. The extensive footnotes, while informative, further contribute to the density of the information.
• Potential improvements: To improve readability, the authors could consider using a more visually distinct way to separate the sections on caffeinated and decaffeinated coffee. Additionally, providing a brief explanation of the "p for trend" in the footnote could be helpful for readers less familiar with this statistical concept. A graphical representation of the main findings, such as a forest plot, could also be a valuable addition to the paper, complementing the detailed information in the table.

TABLE 3 The association with HNC by anatomical subsite for tea drinking status...

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TABLE 3 The association with HNC by anatomical subsite for tea drinking status and daily tea consumption among HNC cases and controls from select INHANCE consortium studies.

Figure/Table Image (Page 7)

First Reference in Text

Tea drinkers had a reduced risk of hypopharyngeal cancer (OR, 0.71; 95% CI, 0.59-0.87) compared with non-tea drinkers (Table 3).

Description

• Purpose of the table: This table investigates the relationship between tea consumption and the risk of head and neck cancer (HNC). Like a detective comparing clues, it examines whether drinking tea is associated with a higher, lower, or similar risk of developing HNC compared to not drinking tea. It breaks down the investigation by looking at specific locations of cancer within the head and neck, referred to as anatomical subsites.
• Structure and organization: The table is organized into rows and columns. The rows represent different categories of tea consumption, such as "non-tea drinker," ">0 to ≤1 cup," and ">1 cup." The columns represent different anatomical subsites of HNC, including "Oral cavity," "Oropharynx," "Hypopharynx," and "Larynx." Each cell at the intersection of a row and column presents data comparing tea drinkers and non-tea drinkers for that specific cancer subsite. It is as if we are dividing a large group of people into smaller groups based on their tea drinking habits and the location of their cancer and then comparing the groups to see if there are any noticeable differences.
• Data presentation and key metrics: For each category of tea consumption and cancer subsite, the table shows the number of "controls" (people without cancer) and "cases" (people with cancer). It also presents the "OR" (Odds Ratio) and "95% CI" (95% Confidence Interval). The OR is a measure of association, like a clue that suggests whether tea drinking is linked to a higher or lower risk of cancer. An OR of 1 suggests no association, while an OR greater than 1 suggests an increased risk and an OR less than 1 suggests a decreased risk. The 95% CI provides a range of values that likely contains the true OR. It's similar to a range of guesses – the narrower the range, the more confident we are about the OR. For example, an OR of 0.71 with a 95% CI of 0.59 to 0.87 means that we are 95% confident that the true OR is between 0.59 and 0.87, suggesting a reduced risk.
• Statistical measures: The table includes "p for heterogeneity" and "p for trend." "P for heterogeneity" checks if the results are consistent across different studies within the INHANCE consortium. A low p-value (less than 0.05) indicates that the results vary significantly between studies. "P for trend" tests if there's a consistent trend between the amount of tea consumed and the risk of cancer. For instance, it checks if drinking more tea is consistently associated with a higher or lower risk. A low p-value (less than 0.05) for the trend test suggests a statistically significant trend, meaning the observed trend is unlikely due to random chance.
• Footnotes and adjustments: The table has footnotes that provide important details about the methodology, such as which studies were included in each analysis and the factors that were adjusted for in the statistical models. These adjustments are like controlling for other variables that could influence the results, such as age, sex, and smoking habits. By adjusting for these factors, we can isolate the specific effect of tea consumption on HNC risk. Footnote 'a', for instance, indicates that the results were adjusted for study center, age, sex, race/ethnicity, education, body mass index, daily cigarette consumption, duration of cigarette consumption, duration of cigar usage, duration of pipe usage, daily alcohol consumption, fruit consumption, and vegetable consumption.

Scientific Validity

• Comprehensive adjustment for confounders: The study adjusts for a wide range of potential confounders, including demographic factors, smoking and alcohol consumption, and dietary factors. This thorough adjustment strengthens the validity of the findings by minimizing the possibility that the observed associations are due to factors other than tea consumption.
• Stratification by anatomical subsite: Similar to Table 2, stratifying the analysis by anatomical subsite is a methodological strength. This allows for a more precise examination of the relationship between tea consumption and HNC risk, acknowledging the heterogeneity of HNC.
• Assessment of dose-response relationship: The inclusion of different categories of tea consumption (">0 to ≤1 cup," ">1 cup") and the calculation of the p-value for trend allow for an evaluation of a potential dose-response relationship. This is important for understanding whether the amount of tea consumed influences the risk of HNC.
• Heterogeneity assessment: The consideration of heterogeneity across studies is crucial for pooled analyses. The use of random-effects models when heterogeneity is present is appropriate and enhances the robustness of the findings.
• Limitations of the analysis: The table does not specify the type of tea consumed (e.g., black, green, oolong). Different types of tea have varying levels of bioactive compounds, which could differentially affect HNC risk. This lack of detail limits the interpretability of the findings. Also, the table only presents the results for two categories of daily tea consumption, which might be insufficient to fully capture the dose-response relationship. There is no category for less than daily consumption.

Communication

• Clarity and organization: The table is well-organized and clearly structured, with distinct sections for tea drinking status and daily tea consumption. The use of bold font for headings and the clear labeling of rows and columns facilitate readability.
• Use of technical terms: The table employs standard epidemiological terms like "Odds Ratio" and "95% Confidence Interval." While these terms are appropriate for a scientific audience, they might be challenging for a lay reader to understand. The footnotes provide some explanation, but a more explicit definition of these terms within the table or caption could be beneficial.
• Density of information: The table presents a substantial amount of data, which can be overwhelming for the reader. The detailed breakdown by anatomical subsite is valuable but contributes to the complexity of the information presented. The numerous footnotes, while necessary, add to the density of the table.
• Potential improvements: To enhance clarity, the authors could consider visually separating the results for different anatomical subsites more distinctly. Additionally, providing a brief explanation of "p for trend" and "p for heterogeneity" in the footnotes would be helpful for readers less familiar with these statistical concepts. A graphical representation of the key findings, such as a forest plot, could complement the detailed information in the table and make the results more accessible to a wider audience.

TABLE 4 ORs for oral cavity and oropharyngeal cancer risk for drinking >4 cups...

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TABLE 4 ORs for oral cavity and oropharyngeal cancer risk for drinking >4 cups of caffeinated coffee daily versus non-coffee drinkers across strata of selected factors from select INHANCE consortium studies.

Figure/Table Image (Page 8)

First Reference in Text

To assess potential effect modifiers for drinking >4 cups of caffeinated coffee daily and oral cavity and oropharyngeal cancers, we conducted a stratified analysis (Table 4).

Description

• Purpose of the table: This table explores whether the relationship between drinking a lot of caffeinated coffee (more than 4 cups a day) and the risk of getting oral cavity and oropharyngeal cancers is different across various groups of people. It's like investigating if a medicine works the same way for men and women, or for younger and older people. In this case, the 'medicine' is drinking more than 4 cups of caffeinated coffee daily, and the 'effect' is the risk of these cancers. The groups are defined by factors like age, sex, smoking habits, and so on. This is referred to as assessing for effect modification.
• Structure and organization: The table is organized with different factors listed on the left-hand side, such as age, sex, tobacco smoking, alcohol intake, fruit intake, vegetable intake, study region, study period, and type of controls. Each factor is divided into categories, or "strata". For example, "age" is split into "<55" and "≥55". For each stratum, the table compares people who drink more than 4 cups of caffeinated coffee a day to those who don't drink coffee. It then shows the "OR" (Odds Ratio) and "95% CI" (95% Confidence Interval) for each group. Each stratum essentially gets its own mini-analysis to see if the coffee-cancer relationship holds true within that specific group.
• Data presentation and key metrics: For each stratum, the table shows the number of cases (people with cancer) and controls (people without cancer) for both coffee drinkers (">4 cups") and non-coffee drinkers. The "OR" (Odds Ratio) is the key metric here. It tells us if drinking a lot of coffee is linked to a higher, lower, or similar risk of cancer within that specific group. An OR of 1 means no difference in risk. An OR greater than 1 suggests an increased risk, while an OR less than 1 suggests a decreased risk. The "95% CI" (95% Confidence Interval) gives us a range of values that likely contains the true OR. Think of it like a net – the wider the net, the less certain we are about where the true OR lies. For example, in the "Age (years)" category, for people aged less than 55, an OR of 0.74 with a 95% CI of 0.59 to 0.93 suggests that drinking more than 4 cups of coffee is associated with a reduced risk of these cancers in this age group, and we are 95% confident the true OR lies within that range.
• Footnotes and adjustments: The table has footnotes that provide important details. Footnote 'a' explains that the analyses were adjusted for several factors, including study center, age, sex, race/ethnicity, education, body mass index, and so on. These adjustments are crucial because they help isolate the specific effect of coffee consumption on cancer risk, separate from other potential influences. It's like making sure we're comparing apples to apples and not apples to oranges. Footnote 'b' indicates that the analysis does not include the Saarland study due to sparse stratum data. Footnote 'c' indicates that the sum of cases and controls may not add up to the total due to missing values. These footnotes are important for understanding the limitations and nuances of the analysis.

Scientific Validity

• Appropriateness of stratified analysis: Conducting a stratified analysis is a valid and important approach to assess effect modification. By examining the association between coffee consumption and cancer risk within different subgroups, the researchers can identify potential variations in the effect that might be masked in an overall analysis.
• Selection of stratification factors: The factors chosen for stratification (age, sex, tobacco smoking, alcohol intake, etc.) are relevant and commonly investigated as potential effect modifiers in cancer epidemiology. These factors are known to be associated with HNC risk and could plausibly interact with coffee consumption.
• Adjustment for confounders: The adjustment for multiple confounders in each stratum-specific analysis is crucial for controlling for potential biases and isolating the specific effect of coffee consumption. The comprehensive list of adjusted factors strengthens the validity of the findings.
• Limitations of the analysis: The table only examines the effect modification for the highest category of coffee consumption (">4 cups"). It would also be informative to investigate effect modification for other levels of consumption. Additionally, the exclusion of the Saarland study due to sparse data might limit the generalizability of the findings. The statistical power to detect effect modification might be limited in some strata with small numbers of cases and controls.

Communication

• Clarity of presentation: The table is generally well-organized and easy to understand. The clear labeling of rows and columns, and the use of bold font for subheadings, enhance readability. The presentation of data for each stratum allows for a straightforward comparison of ORs across different groups.
• Use of technical terms: The table uses appropriate technical terms like "Odds Ratio" and "95% Confidence Interval." While these terms are standard in epidemiological reporting, they might be challenging for a lay reader. The caption provides some context, but a more explicit definition of these terms within the table or caption could be beneficial.
• Density of information: The table presents a large amount of data, which can be somewhat overwhelming. However, the clear organization and the focus on a single exposure-outcome relationship (coffee consumption and oral/oropharyngeal cancer risk) make the information manageable.
• Potential improvements: To enhance clarity, the authors could consider providing a brief explanation of "effect modification" in the caption or footnotes. Additionally, a graphical representation of the stratum-specific ORs, such as a forest plot, could complement the table and make the results more accessible. Including the p-values for interaction would also provide a more formal statistical assessment of effect modification.

FIGURE 1 Study-specific odds ratios for >4 cups of caffeinated coffee daily...

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FIGURE 1 Study-specific odds ratios for >4 cups of caffeinated coffee daily versus non-coffee drinkers for oral cavity and oropharyngeal cancers.

Figure/Table Image (Page 9)

First Reference in Text

Figure 1 shows study-specific OR for drinking >4 cups of caffeinated coffee daily compared to non-coffee drinkers for oral cavity and oropharyngeal cancers combined.

Description

• Purpose of the figure: This figure is a visual representation of how drinking more than 4 cups of caffeinated coffee per day is associated with the risk of oral cavity and oropharyngeal cancers, compared to not drinking coffee. It shows the results from different individual studies that are part of the larger INHANCE consortium. You can think of it like a summary of different polls on the same topic – each poll gives its own result, and the figure shows all these results together.
• Structure and components: The figure is a type of graph called a forest plot. On the left side, it lists the names of the individual studies, along with the years they were conducted. Each study gets its own horizontal line. On each line, there's a square that represents the study's result, called the "Odds Ratio" (OR). The size of the square reflects the weight of the study in the overall analysis, which often relates to the study's sample size. Bigger squares mean the study has a larger influence on the overall result. There are also horizontal lines extending from each square, which represent the "95% Confidence Interval" (CI) – a range of values that likely contains the true OR. It's like saying, "We're pretty sure the real answer is somewhere between this lower value and this higher value." The position of the square and the length of the horizontal lines are important. If the square is to the left of the vertical line at 1, it suggests that coffee drinking is associated with a reduced risk of cancer in that study. If it's to the right, it suggests an increased risk. If the horizontal line crosses the vertical line at 1, it means the result is not statistically significant.
• Key metrics: Odds Ratio (OR) and 95% Confidence Interval (CI): The "Odds Ratio" (OR) is a measure of association between an exposure (drinking coffee) and an outcome (cancer). An OR of 1 means there's no association – coffee drinking doesn't change the risk. An OR less than 1 suggests that coffee drinking is associated with a reduced risk of cancer, while an OR greater than 1 suggests an increased risk. The "95% Confidence Interval" (CI) gives us a range of values that likely contains the true OR. For example, if a study has an OR of 0.5 with a 95% CI of 0.3 to 0.8, it means that in that study, coffee drinkers had half the risk of cancer compared to non-coffee drinkers, and we're 95% confident that the true OR is between 0.3 and 0.8. If the CI includes 1, as in a range of 0.8 to 1.2, it means the result is not statistically significant – we can't be sure if coffee increases or decreases the risk.
• Overall summary and heterogeneity: At the bottom of the figure, there's a diamond shape that represents the overall result when all the studies are combined. This is called a "pooled" or "summary" OR. The width of the diamond represents the 95% CI for the overall result. The figure also provides information about "heterogeneity," which is a measure of how different the results of the individual studies are. It's like checking if the polls agree with each other. The I² value tells us the percentage of variation across studies that is due to heterogeneity rather than chance. A higher I² value (closer to 100%) means more heterogeneity. The p-value for heterogeneity tells us if the differences between the studies are statistically significant. A low p-value (less than 0.05) suggests significant heterogeneity.

Scientific Validity

• Appropriateness of using a forest plot: A forest plot is an appropriate and standard way to present the results of multiple studies in a meta-analysis. It allows for a visual comparison of study-specific ORs and their CIs, as well as an assessment of heterogeneity.
• Selection of studies: The figure includes studies from the INHANCE consortium, which is a large and well-established collaboration. The selection of studies appears to be appropriate, given the research question.
• Calculation of the overall OR: The overall OR is calculated using an inverse-variance weighted model, which is a standard method for combining study-specific ORs in a meta-analysis. This method gives more weight to studies with larger sample sizes and more precise estimates.
• Assessment of heterogeneity: The assessment of heterogeneity using the I² statistic and the p-value is important for understanding the consistency of the findings across studies. The reported I² of 0.0% suggests low heterogeneity, indicating that the study results are quite consistent with one another.
• Limitations: While the forest plot provides a good overview of the study-specific ORs, it does not provide information on the potential sources of heterogeneity (if any). Further analyses, such as subgroup analyses or meta-regression, might be needed to explore potential effect modifiers.

Communication

• Clarity of presentation: The forest plot is generally clear and well-organized. The use of squares to represent ORs and horizontal lines for CIs is standard and easy to understand. The labeling of the studies and the inclusion of the overall OR and heterogeneity statistics are helpful.
• Use of technical terms: The figure uses technical terms like "Odds Ratio" and "95% Confidence Interval," which are appropriate for a scientific audience. However, a brief explanation of these terms in the caption or the figure legend would be beneficial for readers who are not familiar with meta-analysis.
• Visual appeal and readability: The figure is visually appealing and easy to read. The use of different sizes of squares to represent study weights is effective. The alignment of the squares and the horizontal lines makes it easy to compare the results across studies.
• Potential improvements: To enhance clarity, the authors could consider adding a vertical line at the null value (OR=1) to make it easier to see which studies show a statistically significant association. Additionally, providing a brief explanation of the I² statistic and the p-value for heterogeneity in the figure legend would be helpful. It might also be useful to include the number of cases and controls for each study in the figure or a separate table.

Discussion

Key Aspects

• Updated Findings on Coffee and HNC Risk: This updated pooled analysis from the INHANCE consortium reveals new associations between coffee consumption and reduced risk of head and neck cancer (HNC). Specifically, drinking more than 4 cups of caffeinated coffee daily was inversely associated with the risk of HNC overall, oral cavity cancer, and oropharyngeal cancer. Furthermore, consuming 3-4 cups daily was linked to a reduced risk of hypopharyngeal cancer. These findings build upon previous research, providing a more detailed understanding of the relationship between coffee consumption and specific HNC subsites.
• Decaffeinated Coffee and Oral Cavity Cancer: The study found an inverse association between decaffeinated coffee consumption and oral cavity cancer risk. This finding is significant because previous studies often lacked sufficient data to analyze decaffeinated coffee separately. It suggests that bioactive compounds other than caffeine, such as polyphenols, may contribute to the potential anticancer effects of coffee.
• Tea Consumption and HNC Risk: Tea consumption was found to be inversely associated with the risk of HNC overall and hypopharyngeal cancer, particularly for those consuming between >0 to \u22641 cup daily. However, an increased risk of laryngeal cancer was observed among individuals drinking more than 1 cup of tea per day. This highlights the complex relationship between tea consumption and HNC risk, which may vary depending on the specific subsite.
• Comparison with Existing Literature: The study's findings on caffeinated coffee are consistent with previous meta-analyses and the prior INHANCE study, which reported an inverse association between caffeinated coffee and oral cavity and pharyngeal cancers. However, the current study provides a more granular analysis by examining oropharyngeal and hypopharyngeal cancers separately, revealing a protective association for both subsites. The findings on tea are more nuanced, with some inconsistencies compared to previous research, potentially due to differences in tea types and study populations.
• Potential Mechanisms: The study discusses potential mechanisms underlying the observed associations. For coffee, the presence of bioactive compounds like polyphenols, which have antioxidant and anticancer properties, is proposed as a contributing factor. For tea, the potential for theophylline to mediate gastroesophageal reflux disease (GERD) is suggested as a possible explanation for the increased risk of laryngeal cancer observed with higher tea consumption.
• Stratified and Sensitivity Analyses: The study conducted stratified and sensitivity analyses to assess the robustness of the findings. The inverse association between high caffeinated coffee consumption and oral cavity/oropharyngeal cancers remained consistent across various subgroups, including age, sex, tobacco/alcohol use, and dietary factors. The sensitivity analysis demonstrated that the overall risk estimates were not unduly influenced by any single study.
• Strengths and Limitations: The study acknowledges its strengths, including the large sample size from the INHANCE consortium, the inclusion of new studies, and the detailed information on coffee and tea consumption. Limitations are also discussed, such as the potential for recall bias and misclassification in case-control studies, data harmonization challenges, and the limited generalizability due to the predominantly North American and European study populations.
• Future Research Directions: The study concludes by highlighting the need for future research to investigate the effects of coffee and tea consumption in diverse populations, particularly in low- and middle-income countries with a high burden of HNC. Further research should also explore the role of different coffee and tea types, processing styles, and other factors like beverage temperature to better understand the mechanisms underlying the association between these beverages and HNC risk.

Strengths

• Comprehensive Discussion of Findings

  The Discussion section effectively summarizes and interprets the study's findings, placing them within the context of existing literature and highlighting new contributions.

  "In this updated pooled case-control analysis from the INHANCE consortium, new associations were observed." (Page 7)
• Consideration of Potential Mechanisms

  The section thoughtfully explores potential biological mechanisms that may explain the observed associations between coffee/tea consumption and HNC risk.

  "Polyphenols, bioactive compounds found in caffeinated coffee, decaffeinated coffee, and tea, have exhibited antioxidative" (Page 8)
• Acknowledgment of Study Limitations

  The Discussion section transparently acknowledges the limitations of the study, including potential biases and generalizability concerns.

  "Potential limitations should also be considered." (Page 10)
• Clear Future Research Directions

  The section provides clear and well-justified recommendations for future research, emphasizing the need for studies in diverse populations and further investigation into different coffee/tea types.

  "Further studies should assess the effects of coffee and tea consumption in regions beyond North America and Europe" (Page 10)

Suggestions for Improvement

• Expand on Dose-Response Relationship Discussion

  This medium-impact improvement would provide a more nuanced understanding of the relationship between coffee/tea consumption and HNC risk. While the Discussion mentions dose-response relationships, it could benefit from a more in-depth exploration of this aspect, particularly regarding the varying effects observed across different consumption levels and HNC subsites. This aligns with the Discussion section's role in interpreting the findings and placing them within a broader context. Elaborating on the dose-response findings would strengthen the paper by providing a more complete picture of the complex relationship between coffee/tea intake and HNC risk. This could involve discussing potential thresholds for protective effects, the implications of different consumption patterns, and how these findings compare with other studies that have examined dose-response relationships. This would enhance the reader's understanding of the study's implications and inform future research directions. Ultimately, a more comprehensive discussion of the dose-response relationship would provide a more nuanced interpretation of the findings and highlight the importance of considering consumption levels in future studies.

  "Dose-response relationships were observed between drinking >4 cups of caffeinated coffee daily and decreased risks of HNC" (Page 9)

  Implementation: Add a paragraph specifically addressing the dose-response findings. For example: "The observed dose-response relationships warrant further discussion. For caffeinated coffee, the protective effect appeared to strengthen with increasing consumption, particularly for oral cavity and oropharyngeal cancers. This suggests a potential threshold effect, where higher levels of intake may be necessary to confer significant risk reduction. In contrast, the dose-response relationship for tea was more complex, with a protective effect observed at lower consumption levels for overall HNC and hypopharyngeal cancer, but an increased risk of laryngeal cancer at higher consumption. These findings highlight the need for future studies to carefully examine dose-response patterns and to consider potential variations across HNC subsites."

• Further Explore Laryngeal Cancer Finding

  This high-impact improvement would address a critical finding that requires further explanation and contextualization. While the Discussion briefly mentions a potential mechanism for the increased risk of laryngeal cancer with higher tea consumption, it could benefit from a more thorough exploration of this finding, including a discussion of alternative explanations and potential confounding factors. This is crucial for a Discussion section, which should provide a comprehensive interpretation of the results. Expanding on the laryngeal cancer finding would strengthen the paper by demonstrating a more in-depth consideration of this unexpected result. This could involve discussing other studies that have examined the relationship between tea consumption and laryngeal cancer, exploring potential biases or limitations that may have influenced this finding, and considering the role of other factors, such as tea temperature or specific tea types. This would provide a more balanced and nuanced interpretation of the study's findings. Ultimately, a more thorough discussion of the laryngeal cancer finding would enhance the paper's credibility and provide a more complete understanding of the complex relationship between tea consumption and HNC risk.

  "A potential mechanism for tea consumption and increased laryngeal cancer risk is mediation by gastroesophageal reflux disease (GERD)." (Page 9)

  Implementation: Add a paragraph specifically addressing the laryngeal cancer finding. For example: "The increased risk of laryngeal cancer associated with higher tea consumption warrants further investigation. While the potential role of theophylline-mediated GERD is a plausible mechanism, other factors should also be considered. For instance, the temperature of consumed tea has been linked to an increased risk of esophageal and gastric cancers in some studies, and it is possible that this could also play a role in laryngeal cancer. Additionally, specific types of tea, such as black tea, which is more commonly consumed in the study populations, may contain compounds that could potentially increase laryngeal cancer risk. Further research is needed to explore these possibilities and to determine whether this finding is specific to certain populations or tea consumption patterns."

• Discuss Implications for Public Health Recommendations

  This medium-impact improvement would enhance the practical relevance of the study. While the Discussion focuses on interpreting the findings and suggesting future research, it could also briefly discuss the potential implications of these findings for public health recommendations regarding coffee and tea consumption. This aligns with the broader purpose of a Discussion section, which is to consider the study's implications beyond the immediate research context. Adding a brief discussion of public health implications would strengthen the paper by connecting the findings to real-world applications. This could involve considering whether the observed associations are strong enough to warrant specific recommendations regarding coffee and tea intake for HNC prevention, and how these recommendations might be tailored to specific populations or risk groups. This would enhance the paper's impact and relevance to public health professionals. Ultimately, discussing the potential implications for public health recommendations would provide a more practical perspective on the study's findings and highlight their potential contribution to cancer prevention efforts.

  "In conclusion, our findings support associations on the protective effects of coffee and tea consumption on HNC risk." (Page 10)

  Implementation: Add a paragraph discussing the potential public health implications. For example: "While the findings suggest a potential protective effect of coffee and, to a lesser extent, tea consumption against certain HNC subsites, it is premature to make definitive public health recommendations based on this study alone. The observed associations, particularly for coffee, are encouraging and warrant further investigation in diverse populations and with different exposure assessment methods. If these findings are confirmed, they could potentially inform public health strategies aimed at reducing HNC risk, particularly in high-risk populations. However, it is important to consider the potential risks and benefits of coffee and tea consumption in the context of overall health and to avoid making sweeping recommendations based on a single study."