Study Population

The design of the PLCO Cancer Screening Trial has been described.^17,18 In brief, the PLCO trial is a population-based prospective cohort study. Involving approximately 155,000 participants aged 55-74 years from 1993 to 2001, the trial evaluated cancer screening and risk factors. Participants were randomized to intervention (screened for cancers in the first 3-4 years) and control (usual care) arms. Cancer diagnoses were tracked until 2009 and mortality until 2018. All participants completed a baseline questionnaire on demographics, lifestyle, medical history, etc and a dietary history questionnaire (DHQ) for dietary data.

All participants provided informed consent. The PLCO trial received approval from the institutional review boards of all 10 participating centers and the NCI. The current secondary analysis project of PLCO trial data was approved by the NCI’s Cancer Data Access System (Protocol PLCO-1829) and the Institutional Review Board of Chongqing University Cancer Hospital (CZLS2025063-A).

For the present study, we included participants who completed the baseline questionnaire and DHQ at study entry if they were randomized after 1998 or during the subsequent follow-up if they were randomized before 1998. Excluded individuals were those who did not complete the baseline questionnaire, had prior lung cancer or any other cancer history before completing the baseline questionnaire, did not submit a valid DHQ (refer to the dietary assessment section below), or were lost to follow-up after enrollment. Figure 1 shows the participant flowchart, and the Supplemental Table lists details summarized by the NCI.

Dietary Assessment

We assessed dietary intake using the original DHQ, a validated, self-administered food frequency questionnaire developed by the NCI.^19,20 Nutrient intake calculations were based on DHQ responses and used nutrient composition databases generated by the NCI’s Diet*Calc software, relying on data from the US Department of Agriculture’s 1994-1996 Continuing Survey of Food Intakes by Individuals and the University of Minnesota’s Nutrition Data System for Research.²¹ The Healthy Eating Index-2015 (HEI-2015), a measure of diet quality, was calculated using the method described in the literature.²² Additional details regarding the DHQ are included in the Supplemental Appendix.

Calculation of Glycemic Index and Glycemic Load

The GI and GL values for each food were assigned according to the latest international tables of values, with optimal match being sought, as described previously.²³ Glycemic load values for 225 food groups were calculated using the weighted mean method. The dietary GL for each participant was determined by multiplying the GL of each food by its daily consumption frequency. Daily GI was then calculated by dividing GL by the total intake of available carbohydrates (total carbohydrates minus total dietary fiber) and multiplying the result by 100. Additional details regarding GI and GL are included in the Supplemental Appendix.

Ascertainment of Lung Cancer

This study’s primary end point was lung cancer incidence. Participants reported cases via annual questionnaires, initially identified via screenings, self-reports, family reports, and data linkages with cancer registries and the US Centers for Disease Control and Prevention’s National Death Index. All cases were confirmed via pathology reports and categorized into histologic subtypes, including non–small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), according to International Classification of Diseases for Oncology, 2nd Edition morphology.²⁴ Notably, carcinoid lung cancer was not targeted for screening in the PLCO trial.

Assessment of Other Variables

We collected demographic, medical history, and risk factor data via the baseline questionnaire. Hypertension was defined as systolic blood pressure >140 mm Hg, diastolic blood pressure >90 mm Hg, or antihypertensive therapy. Diabetes was defined as fasting glucose >7 mmol/L or antidiabetic therapy. The data gathered included sex, baseline age, body mass index (BMI [kg/m²]), smoking status (current, ever, or never), employment status (working, retired, unemployed), race and ethnicity (Hispanic, non-Hispanic Black, non-Hispanic White, other), family history of any cancer (yes or no), family history of lung cancer (yes or no), physical activity level (less than once per month vs more than once per month), marital status (single, married, no longer married), and educational attainment (no high school diploma, high school diploma, some college, college degree or postgraduate degree).

Statistical Analysis

Baseline characteristics of the study population are presented by GI and GL quartile, comparing the highest (4^th quartile [Q4]) and lowest (1^st quartile [Q1]) groups. We assessed differences using the Student t test for continuous variables and the χ² test for categorical variables.

Individual follow-up time was measured from study entry until lung cancer diagnosis or censoring (death, loss to follow-up, or study end). Multivariable Cox regression estimated hazard ratios (HRs) and 95% CIs for GI/GL and lung cancer risk, using the lowest quartile as reference. Linear trend tests assigned median values to categories, treating them as continuous in the model. Confounders were selected based on literature and statistical criteria. Model 1 adjusted for sex, age, race, and family lung cancer history. Model 2 added study arm, calories, hypertension, diabetes, smoking, alcohol intake, HEI-2015 score, employment, marital status, physical activity, and BMI. Hazard proportionality was verified with Schoenfeld residuals. We also estimated HR increase per 1-SD increase in GI/GL.

We used Kaplan-Meier curves adjusted for confounding factors to depict the risk of lung cancer with GI and GL. We also performed subgroup analyses to assess the heterogeneity of findings, stratified by age (≥65 years vs <65 years), sex (male vs female), family history of lung cancer (yes vs no), BMI category (≥25 kg/m² vs <25 kg/m²), and smoking status (current and former smokers vs never smokers). The P value for interaction was derived from a likelihood ratio test, which compared models with and without interaction terms included.

All analyses were performed using Stata 15 (StataCorp LLC) and IBM SPSS Statistics 23.0. A 2-sided P value <.05 was considered statistically significant, following a predefined statistical analysis plan (available on request).

Characteristics of Study Population

The present study comprised 101,732 participants (50,187 male; 51,545 female), with a mean age of 62.5 years. Dietary GI and GL ranged from 33.0 to 79.2 and 9.7 to 560.9, respectively. Study population baseline characteristics are presented in Table 1, by Q1 and Q4 and GI and GL. Participants in Q4 were more likely to be male, current or ever smokers, Black, married, retired, engaging in less physical activity (for GI), with diabetes and hypertension (for GI), with a lower level of education and lower HEI-2015 scores, and with higher BMI. On average, Q4 participants also consumed more carbohydrates, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, whole grain foods, red meat, added sugar, and sodium and had a higher total caloric intake but a lower intake of magnesium and fruits (for GI) (all P values <.001) (Table 1).

Lung Cancer Events

Over a median 12.2-year follow-up (interquartile range 10.5-13.6 years; 1,213,533 person-years), 1,706 incident lung cancers were identified, comprising 1,473 (86.3%) NSCLC and 233 (13.7%) SCLC cases. No significant differences in histologic subtypes or tumor stages were observed across GI or GL categories (Table 2).

Glycemic Index, Glycemic Load, and Risk of Lung Cancer

After adjusting for demographic, lifestyle, and clinical confounders using Cox regression analysis, participants in GI Q4 had a 13% increased risk of lung cancer (HR 1.13; 95% CI, 1.05-1.31), an 11% increased risk of NSCLC (HR 1.11; 95% CI, 1.05-1.29), and a 34% increased risk of SCLC (HR 1.34; 95% CI, 1.02-2.27) compared with those in GI Q1 (Table 3). In contrast, participants in GL Q4 showed significantly decreased risks of lung cancer (HR 0.72; 95% CI, 0.57-0.90) and NSCLC (HR 0.68; 95% CI, 0.53-0.87) compared with those in GL Q1, but no significant association was observed for SCLC (HR 0.90; 95% CI, 0.51-1.58). Figure 2 presents cumulative incidence curves for lung cancer, NSCLC, and SCLC, stratified by whether GI or GL was above or below the median, adjusted for age and sex. In the overall study population, GI and GL were associated with risks of lung cancer, NSCLC, and SCLC in a linear dose-response manner (P for nonlinearity >.05). After full adjustment, each 1-SD increase in GI was associated with a significant 14% increased risk of SCLC (HR 1.14; 95% CI, 1.00-1.31) but a nonsignificant increased trend in risk of lung cancer (HR 1.03; 95% CI, 0.98-1.09) and NSCLC (HR 1.02; 95% CI, 0.96-1.08) (Figure 3). For GL, there was a significant 14% decreased risk of lung cancer (HR 0.86; 95% CI, 0.77-0.96) and NSCLC (HR 0.86, 95% CI 0.77-0.98) but a nonsignificant decreased trend in risk of SCLC (HR 0.84; 95% CI, 0.63-1.11)

We performed subgroup analyses by repeating the multivariable adjusted Cox regression models across different strata, comparing the highest and lowest quartiles for GI or GL. No significant interactions were observed for predefined stratification factors such as age, sex, family history of lung cancer, BMI, or smoking status (P for interaction >.05) (Table 4).

Interpretation and Comparison With Other Studies

High-GI diets increase blood glucose and insulin levels, promoting glucose intolerance, insulin resistance, and hyperinsulinemia.^25,26 These factors might foster cancer development via hyperglycemia-triggered oxidative stress, inflammation, and activation of glycolysis-linked oncogenic pathways.²⁷ Interestingly, we found a negative link between dietary GL and lung cancer risk. Dietary GL combines GI with carbohydrate quantity, reflecting both carbohydrate quality and amount consumed. The differing results for GI and GL highlight the importance of both carbohydrate type and quantity in the diet. High-quality carbohydrates from fruits, vegetables, and white meat might protect against lung cancer. Previous studies on GL and GI and lung cancer risk have yielded inconsistent findings. Our results align with a meta-analysis of 5 cohort studies showing that a high-GI diet increases lung cancer risk, whereas GL shows an inverse link (though based on low-certainty subgroup evidence).⁹ Two other meta-analyses, both including case-control and cohort studies, concluded that GI generally has a positive relation with lung cancer risk, whereas no association between GL and lung cancer risk was observed.²⁸ Based on 10 large prospective cohorts, high dietary GI was associated with an increased incidence of diabetes-related cancers, whereas no such association was observed for GL.²⁹ However, a meta-analysis including 13,385 cases showed no association between high GI or GL intake and lung cancer risk.¹⁰ In addition, data from the Shanghai Women’s and Men’s Health Studies, which included 649 incident lung cancers among women and 663 among men over a follow-up period of approximately 15 years, indicated no association between GI or GL and lung cancer risk.¹⁵ Similarly, both the Southern Community Cohort Study and the National Institutes of Health–AARP Diet and Health Study showed that dietary GL and GI were not independently associated with incident lung cancer risk in large populations.^14,16

To our knowledge, the present study is one of the few prospective analyses to identify an association between GI and GL and lung cancer risk, including 2 major subtypes. This finding can be attributed to improved dietary assessment methods, the use of robust clinical outcomes aligned with standardized diagnostic procedures, and the inclusion of a large sample size with a relatively long follow-up period based on the PLCO cohort study.^28,30 As a caution, residual confounding factors might have obscured any potential beneficial effects. Interestingly, when GI was analyzed categorically (eg, Q1 vs Q4), there was a significant association with lung cancer and NSCLC risk. However, as a continuous variable (per SD), the association was not significant, likely because per-unit changes yield smaller effect sizes and lower statistical power.

Multiple plausible hypotheses might help explain our findings. Diets with a high GI can lead to elevated postprandial blood glucose and insulin levels, promoting glucose intolerance, insulin resistance, and hyperinsulinemia.^26,31 It has been reported that high insulin levels are associated with an increased risk of lung cancer.³² First, the insulin receptor, which is the binding site for both insulin and IGF-1, is over-expressed in lung cancer.³³ As a potent growth factor, bioactive IGF-1 plays a role in cancer development by inhibiting cell apoptosis and promoting cell proliferation after binding to IGF-1 receptors.³⁴ In addition, elevated insulin levels and insulin receptor expression might contribute to Kirsten rat sarcoma–driven lung cancer in mice by interacting with the phosphoinositide 3-kinase signaling pathway.³⁵ Second, insulin resistance is a pathologic condition, and studies have suggested that it is linked to abnormally high levels of growth factors, adipokines, reactive oxygen species, adhesion molecules, and proinflammatory cytokines factors, all associated with neoplastic tissue survival and the development of cancer stem cells.^36-38 Interestingly, inconsistent associations between GI and GL and lung cancer risk might stem in part from differences in underlying dietary patterns. For example, diets high in refined grains, added sugars, and processed foods—characteristic of low-quality carbohydrate patterns with a high GI—have been associated with increased inflammation and increased cancer risk. In contrast, diets rich in legumes, whole grains, and fruits might lead to greater GL values while simultaneously providing fiber, micronutrients, and phytochemicals that could offer protective effects against lung cancer.^39-41 The inverse association between GL and lung cancer might be explained in part by differences in the sources of dietary carbohydrates. Diets with higher GL might include more fiber-rich or low-GI foods, which have been associated with anti-inflammatory and anticarcinogenic properties.⁴² In addition, individuals with higher GL diets might adhere to healthier overall dietary patterns.⁴³ Residual confounding by other lifestyle or dietary factors cannot be excluded.

Strengths and Limitations

This study’s strengths include a large-scale cohort design with comprehensive baseline data on dietary patterns and thorough information on potential confounders, validated methodology for estimating dietary GI and GL using the DHQ, pathology-confirmed lung cancer cases with subtype-specific analyses, exceptional longitudinal follow-up, and a diverse set of sensitivity analyses, which enhance the robustness and credibility of our results. Nevertheless, several limitations of the current study should be acknowledged.

First, the observational nature of this study limits the ability to determine causality and eliminate residual confounding from unmeasured variables. However, the fact that significant findings were observed after comprehensive adjustments for covariates and thorough subgroup analysis underscores the robustness of the conclusions. Second, although the data were acquired prospectively, dietary information was collected cross-sectionally after the baseline questionnaire; thus, the intraperson variability of diet throughout the follow-up period was not considered in the present study and might not reflect long-term dietary habits. In addition, the dietary intake data collected via the DHQ were self-reported by the participants, which can lead to misclassification and recall bias. Hence, the associations were examined based on ranking instead of absolute intake levels. Third, the sample size for certain analyses was relatively small, which could decrease the analytical power. Therefore, additional caution is warranted when interpreting the results. Fourth, even after adjusting for lifestyle factors, individuals with greater GI values were still more likely to have an overall unhealthier diet and lifestyle, which could contribute to the increased risk observed. Finally, the study sample was predominantly White, which might limit the generalizability of the results to other racial or ethnic groups. Further research is needed to assess the association across diverse populations using more precise and dynamic methods for evaluating dietary intake.

Conclusions and Policy Implications

In this large prospective analysis adjusting for lung cancer risk factors, we found that GI was linked to greater risks of lung cancer, NSCLC, and SCLC, whereas GL was inversely associated with lung cancer and NSCLC risk. Though replication in diverse populations and further mechanistic studies are needed, our findings suggest that low-GI and high-GL foods (eg, vegetables, white meat) might offer lung cancer prevention benefits.