Description of first recurrence in advanced stage high grade serous ovarian cancer receiving intraperitoneal versus intravenous systemic treatment
Bibliographic record
Abstract
OBJECTIVES: To investigate the association of adjuvant intraperitoneal (IP) and intravenous (IV) chemotherapy with location and timing of recurrence in patients with advanced high grade serous ovarian cancer (HGSOC). METHODS: This retrospective cohort study includes patients with stage III or IV HGSOC who underwent optimal primary cytoreductive surgery (PCS) and subsequently received paclitaxel and platinum-based chemotherapy, either IP or IV, at a tertiary care institution between 2010 and 2020. We performed adjusted multivariable logistic regressions to evaluate locations of first recurrence, and adjusted Cox proportional hazards models to assess the association of adjuvant chemotherapy administration and progression free survival. RESULTS: 208 patients met inclusion criteria, of whom 152 (73 %) received IP and 56 (27 %) received IV chemotherapy. IP chemotherapy was associated with decreased intraperitoneal recurrence (odds radio (OR) 0.33 (95 % confidence interval (CI) 0.17-0.64). Extraperitoneal disease at diagnosis was the only factor associated with increased extraperitoneal recurrence (OR 4.09 (95 % CI 1.84-9.10)). Presence of lymph node disease at diagnosis and gross residual disease at PCS were associated with increased lymph node recurrence (OR 4.54 (95 %CI 2.35-9.04) and OR 2.43 (95 %CI 1.18-5.11) respectively). After two years, the risk of recurrence was lower for patients who received IP, compared with IV, chemotherapy (HR 0.30 (95 % CI 0.17-0.53)). CONCLUSIONS: For patients with HGSOC after optimal PCS, IP chemotherapy is associated with decreased intraperitoneal recurrence and decreased risk of recurrence after 2 years compared with IV chemotherapy. This highlights its value in peritoneal restricted disease.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".