Follow-Up of Patients Who Are Clinically Disease-Free after Primary Treatment for Fallopian Tube, Primary Peritoneal, or Epithelial Ovarian Cancer: A Program in Evidence-Based Care Guideline Adaptation
Bibliographic record
Abstract
Background: A need for follow-up recommendations for survivors of fallopian tube, primary peritoneal, or epithelial ovarian cancer after completion of primary treatment was identified by Cancer Care Ontario’s Program in Evidence-Based Care. Methods: We searched for existing guidelines, conducted a systematic review (medline, embase, and cdsr, January 2010 to March 2015), created draft recommendations, and completed a comprehensive review process. Outcomes included overall survival, quality of life, and patient preferences. Results: The Cancer Australia guidance document Follow Up of Women with Epithelial Ovarian Cancer was adapted for the Ontario context. A key randomized controlled trial found that the overall survival rate did not differ between asymptomatic women who received early treatment based on elevated serum cancer antigen 125 (CA125) alone and women who waited for the appearance of clinical symptoms before initiating treatment (hazard ratio: 0.98; 95% confidence interval: 0.80 to 1.20; p = 0.85); in addition, patients in the delayed treatment group reported good global health scores for longer. No randomized studies were found for other types of follow-up. We recommend that survivors be made aware of the potential harms and benefits of surveillance, including a discussion of the limitations of CA125 testing. Women could be offered the option of no formal follow-up or a follow-up schedule that is agreed upon by the woman and her health care provider. Education about the most common symptoms of recurrence should be provided. Alternative models of care such as nurse-led or telephone-based follow-up (or both) could be emerging options. Conclusions: The recommendations provided in this guidance document have a limited evidence base. Recommendations should be updated as further information becomes available.
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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 | 0.042 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| 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".