BackgroundThe national Comprehensive Cancer Network has suggested pembrolizumab as a second-line therapy for esophageal squamous cell carcinoma (ESCC) patients with a programmed death ligand-1 (PD-L1) combined positive score (CPS) ≥ 10. However, despite the increased survival rate associated with pembrolizumab in these patient population, the high cost of pembrolizumab may influence its antitumor effect. This study aimed to evaluate the cost-effectiveness of pembrolizumab compared to chemotherapy as second-line treatments for esophageal carcinoma (EC) based on KEYNOTE-181 trial.MethodsA Markov model was constructed using TreeAge 2021 based on three different groups: all intent-to-treat patients (ITT population), patients with ESCC (ESCC population), and patients with a PD-L1 CPS ≥10 (CPS ≥10 population). Incremental cost, Incremental effect, Life-years, quality-adjusted life-years (QALYs) and incremental cost–effectiveness ratio (ICER) were calculated. Analyses were conducted on the setting of a willingness-to-pay threshold of $150,000 from the US perspective.ResultsThe ICERs for pembrolizumab were $157,589.545 per QALY, $60,238.823 per QALY, and $100,114.929 per QALY compared with chemotherapy in the ITT, ESCC, and CPS≥10 populations, respectively. The ICER of the ITT population was higher than $150,000, suggesting that pembrolizumab was not a cost-effective treatment scheme in patients with a PD-L1 CPS ≤ 10 or esophageal adenocarcinoma. The ICER was < $150,000 in the ESCC and CPS≥10 populations, indicating that pembrolizumab was cost-effective in these two subgroups.ConclusionThe determining of pembrolizumab as a cost-effective second-line therapy for EC in the United States depends on the histologic type and PD-L1 expression.

Background The relationship between single nucleotide polymorphisms (SNPs) and ovarian cancer (OC) risk remains controversial. This systematic review and network meta‐analysis was aimed to determine the association between SNPs and OC risk. Methods Several databases (PubMed, EMBASE, China National Knowledge Infrastructure, Wanfang databases, China Science and Technology Journal Database, and China Biology Medicine disc) were searched to summarize the association between SNPs and OC published throughout April 2021. Direct meta‐analysis was used to identify SNPs that could predict the incidence of OC. Ranking probability resulting from network meta‐analysis and the Thakkinstian’s algorithm was used to select the most appropriate gene model. The false positive report probability (FPRP) and Venice criteria were further tested for credible relationships. Subgroup analysis was also carried out to explore whether there are racial differences. Results A total of 63 genes and 92 SNPs were included in our study after careful consideration. Fok1 rs2228570 is likely a dominant risk factor for the development of OC compared to other selected genes. The dominant gene model of Fok1 rs2228570 (pooled OR = 1.158, 95% CI: 1.068–1.256) was determined to be the most suitable model with a FPRP <0.2 and moderate credibility. Conclusions Fok1 rs2228570 is closely linked to OC risk, and the dominant gene model is likely the most appropriate model for estimating OC susceptibility.

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