Metformin to treat breast cancer: an application of the prevalent new-user design for observational studies with no active comparator
Bibliographic record
Abstract
OBJECTIVES: Numerous observational studies have reported significant reductions in cancer outcomes, including breast cancer in women, with metformin use. However, most studies were affected by immortal time bias. We assessed whether metformin use in women diagnosed with breast cancer is associated with lower breast cancer-related and all-cause mortality and illustrate the impact of immortal time bias on the results. STUDY DESIGN AND SETTING: The Clinical Practice Research Datalink was used to identify a base cohort of all women with a new diagnosis of breast cancer and with type 2 diabetes, at least 18 years of age, between 1998 and 2020. We employed the prevalent new-user design to match metformin initiators 1:1 with nonusers on a prior diabetes diagnosis and time-conditional propensity scores. We also used the naïve approach that introduces immortal time when classifying metformin users. Hazard ratios (HRs) and 95% CIs of all-cause and breast cancer-related death were estimated. RESULTS: The base cohort included 13,314 women newly diagnosed with breast cancer and with type 2 diabetes, before (n = 4761) and after (n = 8553) their breast cancer diagnosis, of which 5047 initiated metformin during follow-up. The prevalent new-user design included 4923 metformin initiators and 4923 matched nonusers. The HRs of breast cancer-related and all-cause mortality were 1.12 (95% CI: 0.98-1.28) and 0.96 (95% CI: 0.89-1.05), respectively. The naïve approach, among women with diabetes at cohort entry, which included 1354 metformin users and 3407 metformin nonusers, resulted in adjusted HRs of 0.45 (95% CI: 0.40-0.50) and 0.58 (95% CI: 0.54-0.62) for breast cancer and all-cause mortality. CONCLUSION: In this study, the use of metformin was not associated with a reduced risk of breast cancer-related and all-cause mortality. Using the flawed approach not accounting for immortal time bias, we confirmed the implausible beneficial effects of metformin on breast cancer and all-cause mortality reported in previous studies. PLAIN LANGUAGE SUMMARY: Observational studies have reported that the antidiabetic drug metformin can increase the survival of women with breast cancer. However, these studies were shown to have a flaw in their analysis, called "immoral time bias", known to exaggerate the benefit of a drug. We used a cohort of over 13,000 women with breast cancer to investigate the effectiveness of metformin on reducing mortality in women with breast cancer, using both the flawed and a correct time-matched approach. Using the flawed approach, we confirmed the implausible beneficial effects of metformin on breast cancer-related and on all-cause mortality reported in previous studies. Using the correct time-matched approach, we found that the use of metformin was not associated with these beneficial effects, confirming the impact of the flaw.
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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 | 0.170 | 0.163 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".