Survival outcomes in patients with platinum-resistant (PL-R) ovarian cancer (OC): The Princess Margaret Cancer Centre (PM) experience.
Bibliographic record
Abstract
e17049 Background: PL-R OC is associated with poor prognosis, and clinical trials indicate that overall survival (OS) is less than 12 months. Here, we describe real-world outcomes in patients with PL-R OC. Methods: Patients treated for PL-R OC presenting to PM from 2011-2015 were identified through the Oncology Patient Information System (OPIS) following research ethics board approval. Treatment data were extracted from OPIS. Baseline characteristics and survival data were obtained through linkage with the PM Survival Registry. Data were supplemented through individual chart review. OS was defined as time from first treatment for PL-R OC to date of death or last contact. Univariable and multivariable analyses were performed to assess the effect of patient characteristics (time from diagnosis to platinum resistance, OC subtype, tumor grade, PL-R or platinum-refractory [PL-RF] status, optimal debulking, clinical trial enrolment, number of treatment lines, germline BRCA1/2 status) on OS using cox proportional hazard models. P-values of 0.05 were considered significant. Results: Data from 165 patients with PL-R OC were included. Most patients had high grade (86%) and serous (84%) tumours. BRCA was mutated in 13%, wild-type in 49%, and unknown in 35%. The median number of lines received was 2 (range 1-6). Weekly paclitaxel (41%) and pegylated liposomal doxorubicin (41%) were the most common first-line regimens. Clinical trial participation was 36%. Median OS was 342 days (95% Confidence Interval 285-440), and was longer in PL-R (366 days) compared to PL-RF OC (302 days). Tumor grade and clinical trial participation were significantly associated with OS on univariable but not multivariable analysis. The number of treatment lines received for PL-R OC was independently predictive of OS (hazard ratio 0.63; p < 0.001), but may reflect capacity for continued treatment in surviving patients (immortal time bias). Conclusions: Real-word outcomes in PL-R OC are similar to those observed in clinical trial populations, and are worse in PL-RF disease. Receipt of a greater number of treatments for PL-R disease is associated with longer OS, but may be due to immortal time bias.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".