Abstract P4-14-03: Influence of competing risks of death on the interpretation of adjuvant endocrine therapy trials for breast cancer
Bibliographic record
Abstract
Abstract Background: Early stage, hormone sensitive breast cancer is associated generally with a good prognosis, with only a minority of patients expected to die of breast cancer. Death from causes other than breast cancer can dilute the patients at risk of breast cancer events and result in over-estimation of risk of recurrence and consequently the benefit from breast cancer therapy, a so-called immortal time bias. The MA.17R trial (Goss et al 2016) evaluated the role of extending adjuvant treatment with letrozole from 5 to 10 years. Here we determine the effect of analyzing the MA.17R trial using methods accounting for competing risks. Methods: We compared conventional and competing risk methods for disease-free survival (DFS) and for distant recurrence-free survival (DRFS). In Kaplan-Meier analyses death from any cause was considered an event while cumulative incidence functions (CIFs) assumed death without recurrence to be a competing risk. The complement of the survival function (one minus the survival function) was used to estimate incidence of the primary event of interest. This was compared to estimates obtained using CIFs accounting for the occurrence of competing events. Results: Non-breast cancer death was the most common event defining DFS and DRFS. Over the course of follow-up, there was increasing discrepancy between the risk of disease recurrence measured using Kaplan-Meier and CIF. Among letrozole treated patients the estimated distant recurrence at 5 years of follow-up was 5.4% using CIF and 9.6% using Kaplan-Meier. At 10 years of follow-up, the estimated distant recurrence was 8.4% using CIF and 20.0% using Kaplan-Meier. Similar results were observed for the placebo group (8.5% vs 12.1% at 5 years and 14.8% vs 27.3% at 10 years), and in patients with baseline cardiovascular disease (see Table). Benefit from letrozole on DFS and DRFS was greater when accounting for competing risk (hazard ratio [HR] for DFS 0.66, 95%CI 0.48-0.90; DFRS HR 0.75, 0.50-1.14) compared to the conventional method (DFS HR 0.79, 0.62-0.99; DRFS HR 0.91, 0.70-1.18). In women with baseline cardiovascular risk, the benefits of extended adjuvant letrozole when considering competing risk (DFS HR 0.38, 0.16-0.89; DRFS HR 0.46, 0.16-1.35) were also greater than those observed in the conventional analysis (DFS HR 0.55, 0.32-0.93; DRFS HR 0.59, 0.33-1.04). Treatment with extended letrozole did not influence non-breast cancer death in women who died with disease recurrence (HR 1.06, 0.74 -1.50) or in those with competing risk or censored from the analysis (HR 1.05, 0.73 -1.49). Conclusion: Over the course of follow-up, estimates of DFS and DRFS differ increasingly if measured using Kaplan-Meier or CIF, with CIF estimates of risk being substantially lower. Using a competing risk model, the reduction in distant recurrence at 8 years with extended letrozole is less than 1%. Additional competing risk analyses of the MA.17 (Goss 2006) and MA.27 (Goss 2013) trials are ongoing. Cumulative incidence of disease recurrence in patients with baseline cardiovascular riskTime (years)CIF (%)1-KM (%)Letrozole11.51.534.46.555.813.8Placebo13.53.538.311.8512.520.3 Citation Format: Ethier J-L, Parulekar W, Shepherd L, Summers L, Strasser-Weippl K, Tu D, Amir E. Influence of competing risks of death on the interpretation of adjuvant endocrine therapy trials for breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-14-03.
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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 | 0.488 | 0.692 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".