Abstract PS1-06: High-risk breast cancer in oldest old: Exploring the effect of different treatments on outcomes
Bibliographic record
Abstract
Abstract Background: Octogenarians and nonagenarians diagnosed with breast cancer have a competing risk of death from other causes and their management is frequently found to be discordant with guidelines in comparison to the younger patients, particularly with low-risk disease. There is limited information about the disease trajectory and outcomes of patients with high-risk disease. Thus, this study was conducted. Methods: This is a retrospective, population-based observational study. Women aged 80 years of age or older and diagnosed with non-metastatic, high-risk breast cancer in Alberta, Canada between January 2004 and December 2017 were identified from the Alberta Cancer Registry. High-risk disease was defined as having any of the following; T3/4, any N positive, triple negative, or Her-2 positive disease. A risk scoring system was generated based on the presence of two anatomical and one biological high-risk features to generate 3 risk levels. Patients’ characteristics (age, Charlson comorbidity index, residence, education-, and income- quintiles), disease characteristics (stage, grade, receptor status,) treatment patterns (treatment delivered, facility) and survival were determined from linkage with administrative databases (Discharge Abstract Data, National Ambulatory Care Reporting System, and Vital statistics). Treatments were stratified into; none, hormonal treatment only (HT), surgery only (S), and surgery with any adjuvant treatment (S+A). Statistical methods included chi-square and Cox regression models. Association between patient, tumor and treatment variables and survival were assessed with uni- and multivariable analysis. Primary outcome was breast cancer specific survival (BCSS) in patients stratified by different risk levels in relation to the treatment delivered. Results: 1369 patients met the inclusion criteria. The median age was 84 years (interquartile range [IQR] 82-88). After a median follow-up of 35 months (m), 873 (64%) patients had died; 405 (46%) of deaths were due to breast cancer. On multivariable analysis, patients had a lower hazard of death from cancer if they were treated with S (HR = 0.51, 95%CI: 0.34, 0.77, p = 0.001) or S+A (HR = 0.41, 95%CI: 0.28, 0.6, p < 0.001) in comparison to HT alone. Patients who did not receive any form of treatment were more likely to die from breast cancer (HR 2.14 95%CI: 1.38, 3.31, p = 0.0006). Patients who had 1 or 2 risk features had higher cancer specific and overall survival if they had S or S+A (49/31m, 92/66m median differences respectively p < .0001). Those with 3 risk features showed longer survival if they received S+A (29/25m median differences p < .0001). Conclusions and Relevance: Our findings suggest that a significant proportion of older patients with breast cancer patients with high-risk features may have increased disease-specific mortality risk. Based on a priori risk levels, and in properly selected patients, treatment options including surgery and adjuvant treatment may be associated in longer survival. Table 1 - Population and Treatment CharacteristicsVariablesCategoryTotal (N=1369)Age group80-85817 (59.7 %)86-90388 (28.3 %)91-95146 (10.7 %)>9518 (1.3 %)Charlson Comorbidity Index0453 (33.1 %)1361 (26.4 %)>=2555 (40.5 %)TNM stageI239 (17.5 %)II663 (48.4 %)III422 (30.8 %)T stageT1416 (30.4 %)T2601 (43.9 %)T3163 (11.9 %)T4169 (12.3 %)Unknown20 (1.5 %)N stageN0526 (38.4 %)N1548 (40 %)N2159 (11.6 %)N385 (6.2 %)Unknown51 (3.7 %)Receptor statusER+orPR+andHer2-1071 (78.2 %)Her2+130 (9.5 %)ER-andPR-andHer2-123 (9 %)Unknown45 (3.3 %)Risk levels1922 (67.3 %)2371 (27.1 %)376 (5.6 %)Surgery typeNo surgery215 (15.7 %)BCS364 (26.6 %)Mastectomy790 (57.7 %)Sentinel surgeryno938 (68.5 %)yes431 (31.5 %)Chemotherapyno1337 (97.7 %)yes32 (2.3 %)Radiotherapyno991 (72.4 %)yes378 (27.6 %)Hormonotherapyno659 (48.1 %)yes710 (51.9 %) Citation Format: Abdulla Al-Rashdan, Yuan Xu, Lisa Barbera, Jeffrey Cao, Winson Cheung, Antoine Bouchard-Fortier, MayLynn Quan. High-risk breast cancer in oldest old: Exploring the effect of different treatments on outcomes [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS1-06.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".