Adherence to the World Cancer Research Fund lifestyle recommendations and incidence of prostate cancer in UK Biobank
Bibliographic record
Abstract
In their recent analysis of the UK Biobank data, Byrne and colleagues1 reported that adherence to the 2018 World Cancer Research Fund/American Institute of Cancer Research (WCRF/AICR) lifestyle recommendations was associated with an ‘increase’ in the risk of prostate cancer (Figure 2 and Supplementary Table S4, available as Supplementary data at IJE online: hazard ratio, 1.04; 95% CI, 1.01, 1.07). The authors acknowledge that this finding was inconsistent with the majority of earlier studies that found null or inverse associations between lifestyle behaviours and prostate cancer risk.1 They speculate that ‘healthy volunteer bias’ may have played a role in the results—implying that men recruited into the study were healthier at baseline than men in the general population of interest; however, the authors do not elaborate on this point. We believe that detection bias warrants consideration as a potential explanation for the findings, wherein men who were more health conscious, i.e. men who reported greater adherence to WCRF/AICR lifestyle recommendations, were also more likely to seek preventive healthcare measures such as prostate-specific antigen (PSA) testing and hence were more likely to undergo a diagnostic biopsy. Specifically, in prostate cancer, the vast majority of cancers are detected at an asymptomatic stage due to PSA testing. Indeed, the advent of PSA screening in the USA in the late 1980s and early 1990s, despite lacking a well-organized national-level screening programme, nonetheless substantially increased prostate cancer incidence, indicating that the strongest risk factor for a prostate cancer diagnosis is undergoing PSA testing. As such, risk factors that are associated with health-seeking behaviours (e.g., greater adherence to WCRF/AICR lifestyle recommendations) may be linked to increased medical care and subsequently increased prostate cancer detection. This phenomenon makes the study of prostate cancer aetiology particularly challenging. A potential solution to this problem is to study the grade of the cancer at diagnosis. Since PSA testing detects more indolent (i.e. lower-grade cancers), studying the tumour grade can shed some light on the risk factors for aggressive, potentially fatal, prostate cancers. Though there is some inconsistency in the evidence for lifestyle behaviours and risk of high-grade and aggressive prostate cancer subtypes,2 in numerous analyses in which distinctions have been made, compared with non-aggressive prostate cancer control groups, the risk of aggressive prostate cancer has been inversely associated with healthy dietary patterns,3 increased physical activity4 and increased adherence to 2007 WCRF/AICR recommendations.5 Similarly, in studies with control groups comprising men not diagnosed with cancer, the risks of aggressive and/or high-grade prostate cancer have been shown to be inversely associated with healthy lifestyle behaviours and positively associated with diets characterized as unhealthy (e.g. dietary patterns that are hyperinsulinaemic and pro-inflammatory), whereas results for non-aggressive and/or low-grade prostate cancers have been null.6–8 Prostate cancer is known to be a biologically heterogeneous disease and it has been suggested that aetiologies may vary across tumour subtypes with respect to modifiable risk factors. To this end, supportive evidence is also emerging from metabolomic studies that have identified lifestyle-related metabolic profiles associated with aggressive prostate cancers but not less aggressive tumour subtypes.9,10 Unfortunately, in the study by Byrne et al.,1 tumour-grade data were not presented to tease apart such associations. Since the diagnosis of aggressive and high-grade prostate cancer is less likely to be associated with health-seeking behaviour than the diagnosis of ‘overall prostate cancer’, studies that distinguish between tumour subtype are better positioned to report findings related to lifestyle behaviours of greater clinical relevance. Moreover, most indolent low-grade prostate cancers are now managed without active treatment and thus detecting these cancers early does not improve long-term outcomes for patients, but merely presents a burden to the patient, physician and healthcare system. Until all studies are designed to differentiate between prostate cancer clinical subtypes, e.g. indolent vs aggressive cancers, results from observational studies will continue to be difficult to interpret with respect to associations with modifiable lifestyle variables. To conclude, we believe that detection bias rather than healthy volunteer bias played a role in the findings reported by Byrne et al.1 Furthermore, the results do not provide insight into whether a healthy lifestyle is associated with lower (or higher) risk of aggressive potentially fatal prostate cancer and hence should not be considered as evidence for a lack of benefit associated with adherence to WCRF/AICR lifestyle recommendations. I.C. wrote the first draft; I.C. and S.J.F. co-wrote the final version. None. None declared.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".