Follow-Up for Cervical Cancer: A Program in Evidence-Based Care Systematic Review and Clinical Practice Guideline Update
Bibliographic record
Abstract
BACKGROUND: In 2009, the Program in Evidence-based Care (pebc) of Cancer Care Ontario published a guideline on the follow-up of cervical cancer. In 2014, the pebc undertook an update of the systematic review and clinical practice guideline for women in this target population. METHODS: The literature from 2007 to August 2014 was searched using medline and embase [extended to 2000 for studies of human papillomavirus (hpv) dna testing]. Outcomes of interest were measures of survival, diagnostic accuracy, and quality of life. A working group evaluated the need for changes to the earlier guidelines and incorporated comments and feedback from internal and external reviewers. RESULTS: One systematic review and six individual studies were included. The working group concluded that the new evidence did not warrant changes to the 2009 recommendations, although hpv dna testing was added as a potentially more sensitive method of detecting recurrence in patients treated with radiotherapy. Comments from internal and external reviewers were incorporated. RECOMMENDATIONS SUMMARY: Follow-up care after primary treatment should be conducted and coordinated by a physician experienced in the surveillance of cancer patients. A reasonable follow-up strategy involves visits every 3-4 months within the first 2 years, and every 6-12 months during years 3-5. Visits should include a patient history and complete physical examination, with elicitation of relevant symptoms. Vaginal vault cytology examination should not be performed more frequently than annually. Combined positron-emission tomography and computed tomography, other imaging, and biomarker evaluation are not advocated; hpv dna testing could be useful as a method of detection of recurrence after radiotherapy. General recommendations for follow-up after 5 years are also provided.
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 | 0.012 |
| 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".