Patient, disease, and survival outcomes for stage IB to stage IV cervical cancer—A population study
Bibliographic record
Abstract
BACKGROUND: Factors that impact recurrence in stages IB to IV include larger tumor, high-risk histology, older age, and lymphovascular invasion (LVI); however, local studies on risk factors for recurrence in British Columbia and our local recurrence patterns have not been well studied. Furthermore, the efficacy of treatment modalities including surgery and chemoradiation in the different stages of cervical cancer have not been clarified in this population. OBJECTIVES: The purpose of this study is to determine the disease and treatment characteristics of stages IB to IV cervical cancer which are associated with survival differences within British Columbia. METHODS/DESIGN: We performed a retrospective population study. A chart review on cervical cancer patients in British Columbia between 1 January 2010 and 31 December 2017 was done. Demographic data and treatment details were collected. Data were analyzed using multivariate Cox regressions, pairwise comparison using the Log-Rank test, and chi-square tests. RESULTS: We included 780 patients (stage I: 31.5%, II: 20.0%, III: 34.5%, and IV: 3.3%). LVI and p16 negativity were associated with decreased overall survival (OS), and multivariate analyses show them to be independent risk factors for poorer survival. Surgical resection in stage I was associated with improved survival, but not with stages II-IV. The use of radical radiation therapy (RT), brachytherapy, and concurrent chemotherapy were independently associated with improved survival in stages II-IV. Peri-RT chemotherapy was not associated with survival benefit in adeno/adenosquamous carcinoma. There were 180 recurrences (23.1%), mostly distant metastases (42.8%). There were fewer recurrences after resection of tumors <2 cm compared to tumors 2 cm or larger (6.49% vs 31.3%, p = 0.00011). Only 37.7% of recurrence/metastases were treated with first-line carboplatin/paclitaxel/bevacizumab, but it was associated with better OS compared to other regimens (median OS 40.1 vs 24.8 months, p = 0.03). CONCLUSION: A significant portion of patients with localized cervical cancer relapse despite radical therapy, with LVI and p16 negativity associated with poorer survival. Surgical resection may still play a role in stage IB disease, while RT, brachytherapy, and concurrent chemotherapy should be considered first-line therapy in stage II-IV diseases. First-line carboplatin, paclitaxel, and bevacizumab for recurrence shows improved survival.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".