Efficacy and toxicity of PARP inhibitor in elderly patients with homologous recombination-deficient newly diagnosed advanced ovarian cancer: the role of dose modification
Bibliographic record
Abstract
OBJECTIVE: To investigate the impact of age on the progression-free survival (PFS) and dose modification, discontinuation and adverse events of poly (adenosine diphosphate-ribose) polymerase inhibitor (PARPi) maintenance therapy in homologous recombination-deficient (HRD) ovarian cancer patients. METHODS: We analyzed 324 patients with advanced stage III-IV epithelial ovarian cancer who had either BRCA mutation or HRD between July 2019 and November 2022. The primary objective was to evaluate the efficacy of PARPis by comparing PFS between patients who received PARPis and those who did not, specifically within 2 age groups: patients aged <60 years and those aged ≥60 years. The secondary objective included evaluating the rates of dose modification, discontinuation, and occurrence of treatment-emergent adverse events in patients who used PARPis. RESULTS: Of the 324 patients, 139 patients (42.9%) were diagnosed at ≥60 years. The use of PARPis resulted in a significant improvement in PFS in both age groups (hazard ratio [HR]=0.37; p<0.01) for patients aged <60 years (HR=0.41; p<0.01) for those aged ≥60 years. The multivariable Cox proportional hazards analysis revealed no significant difference in the PFS benefit between the 2 age groups (HR=0.95; 95% confidence interval [CI]=0.65-1.37; p=0.76). Dose modifications were more frequent in the elderly cohort (63.9% vs. 46.5%; p=0.04). CONCLUSION: PARPis significantly improved PFS in elderly ovarian cancer patients with BRCA mutations and HRD, with a toxicity profile similar to that of younger patients. Elderly patients benefited from frequent dose modifications without any negative impact on PFS outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".