Adjuvant Therapy in Early-Stage Cervical Cancer Patients with Intermediate-Risk Factors, Comparing Between Chemotherapy and Radiotherapy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Patients with early-stage cervical cancer (ESCC) after radical hysterectomy surgery usually need additional adjuvant treatment, but it depends on the presence or absence of certain risk factors. Factors, such as large tumor size, deep stromal invasion, and lymphovascular space involvement, are classified as intermediate risks. Therefore, postoperative adjuvant concurrent chemo-radiotherapy (CRT) or radiotherapy (RT) is recommended for ESCC with risk factors. However, it remains controversial whether CRT is superior to RT as an adjuvant regimen for postoperative with risk factors. METHODS: A systematic search was performed within PubMed, Cochrane, Science Direct, and Google Scholar databases to research the outcome between CRT and RT in ESCC. Three reviewers independently reviewed titles, abstracts, and full article text to identify studies meeting inclusion and exclusion criteria. If there are any discrepancies, it will be resolved by discussion. In this analysis, the Newcastle–Ottawa scale was used to assess the risk of bias of non-randomized studies. We used review manager 5.4 to calculate the result of 95% CI for the outcomes using odds ratio (OR), random effect model was also used if there is heterogeneity. The primary endpoints of interest are recurrence-free survival (RFS) and overall survival (OS). RESULTS: A total of 14 studies included in qualitative synthesis and meta-analysis with a total of 5.294 patients were identified. Patients who had RT after radical hysterectomy was found to significantly have a more favorable RFS rate with OR 0.57 95% CI (0.38–0.84), p = 0.005; I2 = 63%. Nine studies were found comparing the OS between adjuvant RT and adjuvant CRT in a patient with ESCC with intermediate risk, the result is quite similar favoring adjuvant RT with significantly better OS outcome OR 0.69 95% CI (0.54–0.87), p = 0.002; I2 =34%. 1.526 had hematologic toxicities, 797 were RT and 729 had CRT. The study showed RT had better outcomes with lesser toxicities (OR 0.11, 95% CI [0.03–0.44] p = 0.002; I2 = 91%). Non-hematological toxicity, with a total of 1.463 patients, 799 were RT and 664 had CRT. Random models were used due to heterogeneity. RT is significantly associated with lesser non- hematologic toxicities with OR 0.34, 95% CI (0.18–0.66) p = 0.001; I2 = 65%. DISCUSSION: During the last two decades, there were significant changes in practice to cure uterine cervical cancer. Based on the consistent results generated in several previous randomized controlled trials, cisplatin-based CCRT has become the standard treatment for advanced cervical cancer. A randomized prospective studies by Sedlis et al., randomized FIGO IB patients without residual tumor or involved lymph nodes but with two or more intermediate-risk factors later named the “Sedlis criteria” to receive observation or RT following radical surgery. Adjuvant RT led to a reduction of recurrence rates at the cost of an approximately 4% higher rate of grade 3/4 adverse events. There was no increase in OS but an improvement of long-term RFS. On the other hand, a study found that RFS and OS were significantly improved in the addition of chemotherapy, especially in patients with clinical-stage IA2, IB, and IIA with para-metric invasion, residual tumor and/or lymph node involvement. This study found that RT had better outcomes in RFS and OS, RT also had lesser hematologic toxicity and non-hematologic toxicity. After all, it is prudent to take into account the adverse events as well as the QOL for long-term survivors. CONCLUSION: Adjuvant RT shows a better outcome in RFS and OS. CRT is often associated with greater hematological and non-hematological toxicities. Further high-quality randomized clinical trials with larger sample size comparing the efficacy and toxicity of adjuvant CRT with RT are recommended.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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 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".