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      Association Between Power Morcellation and Mortality in Women With Unexpected Uterine Cancer Undergoing Hysterectomy or Myomectomy

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          Abstract

          <div class="section"> <a class="named-anchor" id="d351244e282"> <!-- named anchor --> </a> <h5 class="title" id="d351244e283">PURPOSE</h5> <p id="d351244e285">Despite concerns that power morcellation may adversely affect prognosis of patients with occult uterine cancer, empirical evidence has been limited and inconclusive. In this study, we aimed to determine whether uncontained power morcellation at the time of hysterectomy or myomectomy is associated with increased mortality risk in women with occult uterine cancer. </p> </div><div class="section"> <a class="named-anchor" id="d351244e287"> <!-- named anchor --> </a> <h5 class="title" id="d351244e288">METHODS</h5> <p id="d351244e290">By linking statewide hospital discharge records with cancer registry data in New York, we identified 843 women with occult endometrial carcinoma and 334 women with occult uterine sarcoma who underwent a hysterectomy or myomectomy for presumed benign indications during the period October 1, 2003, through December 31, 2013. Within this cohort, we compared disease-specific and all-cause mortality of women who underwent laparoscopic supracervical hysterectomy/laparoscopic myomectomy (LSH/LM), a surrogate indicator for uncontained power morcellation, with women who underwent supracervical abdominal hysterectomy and total abdominal hysterectomy (TAH), which did not involve power morcellation. Multivariable Cox regressions and propensity score method were used to adjust for patient characteristics. </p> </div><div class="section"> <a class="named-anchor" id="d351244e292"> <!-- named anchor --> </a> <h5 class="title" id="d351244e293">RESULTS</h5> <p id="d351244e295">Among women with occult uterine sarcoma, LSH/LM was associated with a higher risk for disease-specific mortality than TAH (adjusted hazard ratio [aHR], 2.66, 95% CI, 1.11 to 6.37; adjusted difference in 5-year disease-specific survival, −19.4%, 95% CI, −35.8% to −3.1%). In the subset of women with leiomyosarcoma, LSH/LM was associated with an increased risk for disease-specific mortality compared with supracervical abdominal hysterectomy (aHR, 3.64, 95% CI, 1.50 to 8.86; adjusted difference in 5-year disease-specific survival, −31.2%, 95% CI, −50.0% to −12.3%) and TAH (aHR, 4.66, 95% CI, 1.97 to 11.00; adjusted difference in 5-year disease-specific survival, −37.3%, 95% CI, −54.2% to −20.3%). Among women with occult endometrial carcinoma, there was no significant association between surgical approach and disease-specific mortality. </p> </div><div class="section"> <a class="named-anchor" id="d351244e297"> <!-- named anchor --> </a> <h5 class="title" id="d351244e298">CONCLUSION</h5> <p id="d351244e300">Uncontained power morcellation was associated with higher mortality risk in women with occult uterine sarcoma, especially in those with occult leiomyosarcoma. </p> </div>

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          Minimally Invasive versus Abdominal Radical Hysterectomy for Cervical Cancer

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            Identifying Increased Risk of Readmission and In-hospital Mortality Using Hospital Administrative Data: The AHRQ Elixhauser Comorbidity Index.

            We extend the literature on comorbidity measurement by developing 2 indices, based on the Elixhauser Comorbidity measures, designed to predict 2 frequently reported health outcomes: in-hospital mortality and 30-day readmission in administrative data. The Elixhauser measures are commonly used in research as an adjustment factor to control for severity of illness.
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              Is Open Access

              Evaluation of the Propensity score methods for estimating marginal odds ratios in case of small sample size

              Background Propensity score (PS) methods are increasingly used, even when sample sizes are small or treatments are seldom used. However, the relative performance of the two mainly recommended PS methods, namely PS-matching or inverse probability of treatment weighting (IPTW), have not been studied in the context of small sample sizes. Methods We conducted a series of Monte Carlo simulations to evaluate the influence of sample size, prevalence of treatment exposure, and strength of the association between the variables and the outcome and/or the treatment exposure, on the performance of these two methods. Results Decreasing the sample size from 1,000 to 40 subjects did not substantially alter the Type I error rate, and led to relative biases below 10%. The IPTW method performed better than the PS-matching down to 60 subjects. When N was set at 40, the PS matching estimators were either similarly or even less biased than the IPTW estimators. Including variables unrelated to the exposure but related to the outcome in the PS model decreased the bias and the variance as compared to models omitting such variables. Excluding the true confounder from the PS model resulted, whatever the method used, in a significantly biased estimation of treatment effect. These results were illustrated in a real dataset. Conclusion Even in case of small study samples or low prevalence of treatment, PS-matching and IPTW can yield correct estimations of treatment effect unless the true confounders and the variables related only to the outcome are not included in the PS model.
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                Author and article information

                Journal
                Journal of Clinical Oncology
                JCO
                American Society of Clinical Oncology (ASCO)
                0732-183X
                1527-7755
                September 16 2019
                : JCO.19.00562
                Affiliations
                [1 ]Yale University, New Haven, CT
                [2 ]Columbia University, New York, NY
                [3 ]New York State Department of Health, Albany, NY
                [4 ]University at Albany, State University of New York, Albany, NY
                [5 ]CooperSurgical, Trumbull, CT
                Article
                10.1200/JCO.19.00562
                6901279
                31518176
                dec0dc14-7a9b-47dd-a49e-6ae83a1c392d
                © 2019
                History

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