Cervical Cancer Progression in Patients Waiting for Radiotherapy Treatment at a Referral Center in Ethiopia: A Longitudinal Study
Bibliographic record
Abstract
ABSTRACT Nonmetastatic cervical cancer is a highly curable malignancy, and radiotherapy (RT) remains the mainstay treatment. Early initiation is critical, and the optimal time to initiate RT for cure is 6 weeks, with a reported 15% decrease in 3-year overall survival for those who wait 40 days. There is considerable variation in the waiting time to initiate RT between countries, with a median time of 27.2 days in Ontario, Canada and 108 days in South Africa. Real-world evidence of cancer progression because of treatment delay is scarce in low-income countries. Ethiopia, a country of 120 million, had a single machine at Tikur Anbessa Specialized Hospital (TASH) until it acquired a linear accelerator very recently. This study aimed to assess the extent of delay in receiving RT and the effect of delay on the natural disease court in patients with cervical cancer treated at TASH. This study was conducted at TASH between January 2019 and May 2020 and evaluated patients at different time points before and after RT. All individuals who were diagnosed with cervical cancer (stage IIB to stage IVA) and booked for RT at TASH were included. Concurrent chemoradiotherapy was administered for cervical cancer with weekly cisplatin as a chemotherapy agent. A total of 115 patients were included in this study. The median time between pathologic diagnosis and booking RT was 19 days, and the median time from booking to RT initiation was 458 days. The total median time from diagnosis to treatment was 477 days, and the median time to disease progression was 51 days. During the waiting period for RT, the stage was reassessed for 105 patients. The number of patients in stage IIB, IIA, and IIIB decreased during this period, whereas the number of patients in stage IVA increased from 20 (17.4%) to 30 (26.1%), 2 (1.8%) developed distant metastasis to the lungs (stage IVB), and 37 died before receiving a phone call for RT. Of 115 patients booked to receive CCRT, only 9 (7.8%) received CCRT, 80 (69.9%) received a single shot of palliative RT due to disease progression, and 25 (21.7%) did not receive RT at all. The mean and median survival times were 20.1 months (95% confidence interval [CI], 18.3–22.7) and 21 months (95% CI, 18.3–23.8), respectively. Waiting time, stage at presentation, distant metastasis during the waiting time, hydronephrosis during the waiting time, and type of treatment were significantly associated with survival. Multivariate cox regression using these variables found that patients with stage IIIB were 2.2 times more likely to die than those with stage IIB (adjusted hazards ratio, 2.2; 95% CI, 1.07–4.48), and patients with stage IVA were 20.95 times more likely to die than patients with stage IIB (adjusted hazards ratio, 20.95; 95% CI, 6.26–70.03). Prolonged waiting time increased the mortality rate of cervical cancer by 2.9 (95% CI, 1.07–4.5). This study provides a significant advancement in our understanding of cervical cancer care in low-income countries. The median waiting time diagnosis to treatment was 477 days, whereas the median waiting period for disease progression was 51 days, resulting in unnecessary disease progression, change in treatment intent from curative to palliative, and increased mortality. These findings highlight the need to increase access to RT services in lower-income nations to reduce wait times and provide better cancer care.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".