Systemic Therapy for Recurrent, Persistent, or Metastatic Cervical Cancer: A Clinical Practice Guideline
Bibliographic record
Abstract
BACKGROUND: Systemic therapy options are needed for women with recurrent, metastatic, or persistent cervical cancer. This systematic review and clinical practice guideline were developed to address that need, and to update a 2007 guideline from Cancer Care Ontario's Program in Evidence-Based Care. METHODS: The literature between 2006 and April 2014 in the medline and embase databases, the Cochrane Database of Systematic Reviews (Issue 4, 2014), the Cochrane Central Register of Controlled Trials (Issue 3, 2014), relevant guideline databases, and conference proceedings of the American Society of Clinical Oncology (2007-2013) was searched. A working group developed draft guidelines and incorporated comments and feedback from internal and external reviewers. RESULTS: Four phase iii randomized controlled trials met the inclusion criteria for the review and provided the basis for draft recommendations. Feedback was obtained from Ontario practitioners and others abroad, which led to modifications to the draft recommendations. Three key recommendations were developed. CONCLUSIONS: The working group concluded that all patients should be offered the opportunity to participate in appropriate randomized clinical trials. Cisplatin-paclitaxel, cisplatin-vinorelbine, cisplatin-gemcitabine, and cisplatin-topotecan are recommended combinations for this patient population. The substitution of carboplatin for cisplatin in the foregoing combinations can also be recommended because carboplatin is associated with fewer adverse effects and greater ease of administration. Selection of combination chemotherapy will depend on the toxicity profile, patient preference, and other factors. Finally, bevacizumab in combination with cisplatin-paclitaxel or carboplatin-paclitaxel is recommended for a specific subset of the target population as outlined in Gynecologic Oncology Group study 0240.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".