Abstract P5-13-20: Overall survival of women with breast cancer treated with newly approved targeted drugs in Manitoba: A population based study
Bibliographic record
Abstract
Abstract Background: Cancer drugs are approved based on the results of clinical trials in selected, rigorously monitored groups of participants. The ultimate goal of new cancer drug approvals is to improve outcomes, preferably overall survival, at population level compared to existing standard of care. Methods: We conducted a population based study using data from the provincial Manitoba cancer registry, Manitoba Health, and electronic patient records. We collected data on patient demographics, toxicity outcomes, and efficacy outcomes including recurrence and Overall Survival (OS) of patients who were treated with the 10 most frequently used new targeted cancer drugs between January 2005 and December 2017 in Manitoba. Patient demographics were reported using descriptive statistics. Toxicity events were reported in frequency, and Kaplan-Meier curves were used for time-to-event outcomes. Results: Four breast cancer drugs – Trastuzumab Emtansine (T-DM1), pertuzumab, fulvestrant, and palbociclib qualified for inclusion. During the timeframe, 71 women were treated with T-DM1, 100 with pertuzumab, 102 with Fulvestrant, and 21 with palbociclib. Patient demographics, disease stage, and line of therapy were comparable to those reported in pivotal trials leading to approval of these drugs. Median OS was 15.82 months for T-DM1, 25.34 months for pertuzumab, 14.65 months for fulvestrant, and not assessable for palbociclib – of note, these were consistently about half the median OS duration reported in pivotal trials leading to approval of the respective drugs. [For example, median OS in pivotal trials was 55.6 months for pertuzumab, 29.9 months for T-DM1, up to 26.4 months for fulvestrant, and 37.5 months (one trial) for palbociclib]. Serious toxicities were observed more frequently than reported in the literature – detailed results will be presented. Conclusion: Despite impressive improvements in outcomes reported in clinical trials leading to approval of new targeted therapies for breast cancer, such agents only yield modest OS at population level which was often worse than even the control groups used in pivotal clinical trials. Given the main aim of new interventions are to improve outcomes at population level, future research should explore causes, and identify solutions to minimize such efficacy-effectiveness gaps. Cautious patient selection, early identification and management of toxicities, and increasing resources available to individual patients may minimize such gaps. Citation Format: Devgan S, Bucher O, Geirnaert M, Niraula S. Overall survival of women with breast cancer treated with newly approved targeted drugs in Manitoba: A population based study [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 P5-13-20.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".