Cervical cancer management in a low resource setting: A 10-year review in a tertiary care hospital in Kenya
Bibliographic record
Abstract
Background: Cervical cancer is one of the leading causes of cancer mortality among women in Kenya due to late presentations, poor access to health care, and limited resources. Across many low- and middle-income countries infrastructure and human resources for cervical cancer management are currently insufficient to meet the high population needs therefore patients are not able to get appropriate treatment. Objective: This study aimed to describe the clinicopathological characteristics and the treatment profiles of cervical cancer cases seen at Moi Teaching and Referral Hospital (MTRH). Methods: This was a retrospective cross-sectional study conducted at MTRH involving the review of the electronic database and medical charts of 1541 patients with a histologically confirmed diagnosis of cervical cancer between January 2012 and December 2021. Results: Of the 1541 cases analyzed, 91% were squamous cell carcinomas, 8% were adenocarcinomas, and 1% were other histological types. Thirty-eight percent of the patients were HIV infected and less than 30% of the women had health insurance. A majority (75%) of the patients presented with advanced-stage disease (stage IIB-IV). Only 13.9% received chemoradiotherapy with curative intent; of which 33.8% received suboptimal treatment. Of the 13% who received surgical treatment, 45.3% required adjuvant therapy, of which only 27.5% received treatment. Over 40% of the women were lost to follow-up. Conclusion: Most of the patients with cervical cancer in Kenya present at advanced stages with only a third receiving the necessary treatment while the majority receive only palliative treatment or supportive care.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".