Introduction: Graft versus leukemia (GvL) effect decreases the risk of relapse. The presence of graft versus host disease (GvHD) was previously shown to correlate with the GvL effect. GvHD-related mortality may spuriously lead to this conclusion when regression models are used without adjusting for competing risk of death. Herein, we planned to assess the performance of Fine and Gray proportional hazard model, a commonly used competing risk model in survival analysis, in a simulation study using different GvHD-related mortality rates and across different simulated GvL effects. Methods: We simulated datasets of 500 patients with maximum follow up of 5 years using Weibull distribution with 30% risk for GvHD and relapse. The relapse status was assigned using different simulated impact of GvL effect (simulated Hazard Ratio [HR]: 0.8 to 0.2) and at different GvHD-related mortality (HR: 1.2 to 4.8). We then estimated the HRs from different datasets using the Fine and Gray model. Then, we plotted the estimated HRs against the different GvHD-related mortality at different simulated GvL effects. We used simulation scenarios that are close to the expected actual rates in real datasets. We used STATA 13 for all statistical analyses. Results: Fine and Gray proportional hazard competing risk model overestimated the impact of GvL effect with progressively increasing bias as GvHD-related mortality increases. The median bias in the estimated HR ranged from 0.09-0.34. The maximum median bias was estimated in the dataset with the minimal simulated GvL effect (HR of 0.8) and the minimal median bias was estimated in the dataset with the maximum simulated GvL effect (HR of 0.2). The bias overall increased with increasing GvHD-related mortality across different simulated GvL effect (Figure 1). Conclusion: Fine and Gray proportional hazard competing risk model overestimated the impact of GvL effect with progressively increasing bias as GvHD-related mortality increases. We caution its use in datasets with high GvHDrelated mortality.
Background and study aims Wide-area transepithelial sampling (WATS) is an emerging technique that may increase dysplasia detection in Barrett’s esophagus (BE). We conducted a systematic review and meta-analysis of patients who underwent surveillance for BE assessing the additional yield of WATS to forceps biopsy (FB).
Methods We searched Pubmed, Embase, Web of science, and the Cochrane library, ending in January 2021. The primary outcomes of interest were the relative and absolute increase in dysplasia detection when adding WATS to FB. Heterogeneity was assessed using I2
and Q statistic. Publication bias was assessed using funnel plots and classic fail-safe test.
Results A total of seven studies were included totaling 2,816 patients. FB identified 158 dysplasia cases, whereas WATS resulted in an additional 114 cases. The pooled risk ratio (RR) of all dysplasia detection was 1.7 (1.43–2.03), P < 0.001, I
2 = 0. For high-grade dysplasia (HGD), the pooled RR was 1.88 (1.28–2.77), P = 0.001, I
2 = 33 %. The yield of WATS was dependent on the prevalence of dysplasia in the study population. Among studies with high rates of dysplasia, the absolute increase in dysplasia detection (risk difference, RD) was 13 % (8 %-18 %, P < 0.0001, number needed to treat [NNT] = 8). The pooled RD in HGD was 9 % (2 %-16 %), P < 0.001, NNT = 11. For studies with a low prevalence of dysplasia, RD for all dysplasia was 2 % (1 %-3 %), P = 0.001, NNT = 50. For HGD, the RD was 0.6 % (0.2 %-1.3 %), P = 0.019, NNT = 166.
Conclusions In populations with a high prevalence of dysplasia, adding WATS to FB results in a significant increase in dysplasia detection.
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