Chiaruttini Maria Vittoria, Lorenzoni Giulia, Spolverato Gaya, Gregori Dario
Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, and Vascular Sciences and Public Health, University of Padova, 35128 Padova, Italy.
Department of Surgical Oncological and Gastrointestinal Science, University of Padova, 35128 Padova, Italy.
J Clin Med. 2024 May 31;13(11):3272. doi: 10.3390/jcm13113272.
: Quality-of-life metrics are increasingly important for oncological patients alongside traditional endpoints like mortality and disease progression. Statistical tools such as Win Ratio, Win Odds, and Net Benefit prioritize clinically significant outcomes using composite endpoints. In randomized trials, Win Statistics provide fair comparisons between treatment and control groups. However, their use in observational studies is complicated by confounding variables. Propensity score (PS) matching mitigates confounding variables but may reduce the sample size, affecting the power of win statistics analyses. Alternatively, PS matching can stratify samples, preserving the sample size. This study aims to assess the long-term impact of these methods on decision making, particularly in colorectal cancer patients. : A motivating example involves a cohort of patients from the ReSARCh observational study (2016-2021) with locally advanced adenocarcinoma of the rectum, situated up to 12 cm from the anal verge. These patients underwent either a watch-and-wait approach (WW) or trans-anal local excision (LE). Win statistics compared the effects of WW and LE on a composite outcome (overall survival, recurrence, presence of ostomy, and rectum excision). For matched win statistics, we used robust inference techniques proposed by Matsouaka et al. (2022), and for stratified win statistics, we applied the method proposed by Dong et al. (2018). A simulation study assessed the coverage probability of matched and stratified win statistics in balanced and unbalanced groups, calculating how often the confidence intervals included the true values of WR, NB, and WO across 1000 simulations. : The results suggest a better efficacy of the LE approach when considering efficacy outcomes alone (WR: 0.47 (0.01 to 1.14); NB: -0.16 (-0.34 to 0.02); and WO: 0.73 (0.5 to 1.05)). However, when QoL outcomes are included in the analyses, the estimates are closer to 1 (WR: 0.87 (0.06 to 2.06); WO: 0.93 (0.61 to 1.4)) and to 0 (NB: -0.04 (-0.25 to 0.17)), indicating a negative impact of the treatment effect of LE regarding the presence of ostomy and the excision of the rectum. Moreover, based on the simulation study, our findings underscore the superior performance of matched compared to stratified win statistics in terms of coverage probability (matched WR: 97% vs. stratified WR: 33.3% in a high-imbalance setting; matched WR: 98% vs. stratified WR: 34.4% in a medium-imbalance setting; and matched WR: 99.2% vs. stratified WR: 37.4% in a low-imbalance setting). : In conclusion, our study sheds light on the interpretation of the results of win statistics in terms of statistical significance, providing insights into the application of pairwise comparison in observational settings, promoting its use to improve outcomes for cancer patients.
除了死亡率和疾病进展等传统终点外,生活质量指标对肿瘤患者越来越重要。诸如胜率、赢率和净效益等统计工具使用复合终点来优先考虑具有临床意义的结果。在随机试验中,赢率统计可在治疗组和对照组之间进行公平比较。然而,在观察性研究中,混杂变量会使这些工具的使用变得复杂。倾向评分(PS)匹配可减轻混杂变量的影响,但可能会减少样本量,从而影响赢率统计分析的效能。或者,PS匹配可以对样本进行分层,从而保留样本量。本研究旨在评估这些方法对决策的长期影响,尤其是对结直肠癌患者的影响。:一个具有启发性的例子涉及来自ReSARCh观察性研究(2016 - 2021年)的一组患者,他们患有距肛缘12厘米以内的局部晚期直肠腺癌。这些患者接受了观察等待方法(WW)或经肛门局部切除术(LE)。赢率统计比较了WW和LE对复合结局(总生存期、复发、造口的存在和直肠切除)的影响。对于匹配的赢率统计,我们使用了Matsouaka等人(2022年)提出的稳健推断技术,对于分层赢率统计,我们应用了Dong等人(2018年)提出的方法。一项模拟研究评估了匹配和分层赢率统计在平衡和不平衡组中的覆盖概率,计算了在1000次模拟中置信区间包含WR、NB和WO真实值的频率。:结果表明,仅考虑疗效结局时,LE方法的疗效更好(WR:0.47(0.01至1.14);NB: - 0.16( - 0.34至0.02);WO:0.73(0.5至1.05))。然而,当分析中纳入生活质量结局时,估计值更接近1(WR:0.87(0.06至2.06);WO:0.93(0.61至1.4))和0(NB: - 0.04( - 0.25至0.17)),这表明LE治疗效果对造口的存在和直肠切除有负面影响。此外,基于模拟研究,我们的发现强调了在覆盖概率方面,匹配的赢率统计优于分层赢率统计(在高不平衡设置中,匹配的WR:97% 对分层的WR:33.3%;在中等不平衡设置中,匹配的WR:98% 对分层的WR:34.4%;在低不平衡设置中,匹配的WR:99.2% 对分层 的WR:37.4%)。:总之,我们的研究揭示了赢率统计结果在统计显著性方面的解释,为观察性环境中两两比较的应用提供了见解,促进其用于改善癌症患者的结局。