Efficacy and safety of treatment modalities for cesarean scar pregnancy: a systematic review and network meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Cesarean scar pregnancy may lead to varying degrees of complications. There are many treatment methods for it, but there are no unified or recognized treatment strategies. This systematic review and network meta-analysis aimed to observe the efficacy and safety of treatment modalities for patients with cesarean scar pregnancy. DATA SOURCES: MEDLINE, Embase, and Cochrane Central Register of Controlled Trials were searched from their inception to January 31, 2024. In addition, relevant reviews and meta-analyses were manually searched for additional references. STUDY ELIGIBILITY CRITERIA: Our study incorporated head-to-head trials involving a minimum of 10 women diagnosed with cesarean scar pregnancy through ultrasound imaging or magnetic resonance imaging, encompassing a detailed depiction of primary interventions and any supplementary measures. Trials with a Newcastle-Ottawa scale score <4 were excluded because of their low quality. METHODS: We conducted a random-effects network meta-analysis and review for cesarean scar pregnancy. Group-level data on treatment efficacy and safety, reproductive outcomes, study design, and demographic characteristics were extracted following a predefined protocol. The quality of studies was assessed using the Cochrane risk-of-bias tools for randomized controlled trials and the Newcastle‒Ottawa scale for cohort studies and case series. The main outcomes were efficacy (initial treatment success) and safety (complications), of which summary odds ratios and the surface under the cumulative ranking curve using pairwise and network meta-analysis with random effects. RESULTS: Seventy-three trials (7 randomized controlled trials) assessing a total of 8369 women and 17 treatment modalities were included. Network meta-analyses were rooted in data from 73 trials that reported success rates and 55 trials that reported complications. The findings indicate that laparoscopy, transvaginal resection, hysteroscopic curettage, and high-intensity focused ultrasound combined with suction curettage demonstrated the highest cure rates, as evidenced by surface under the cumulative ranking curve rankings of 91.2, 88.2, 86.9, and 75.3, respectively. When compared with suction curettage, the odds ratios (95% confidence intervals) for efficacy were as follows: 6.76 (1.99-23.01) for laparoscopy, 5.92 (1.47-23.78) for transvaginal resection, 5.00 (1.99-23.78) for hysteroscopic curettage, and 3.27 (1.08-9.89) for high-intensity focused ultrasound combined with suction curettage. Complications were more likely to occur after receiving uterine artery chemoembolization, suction curettage, methotrexate+hysteroscopic curettage, and systemic methotrexate; hysteroscopic curettage, high-intensity focused ultrasound combined with suction curettage, and Lap were safer than the other options derived from finite evidence; and the confidence intervals of all the data were wide. CONCLUSION: Our findings indicate that laparoscopy, transvaginal resection, hysteroscopic curettage, and high-intensity focused ultrasound combined with suction curettage procedures exhibit superior efficacy with reduced complications. The utilization of methotrexate (both locally guided injection and systemic administration) as a standalone medical treatment is not recommended.
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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 | 0.024 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.048 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".