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      Obesity and Baseline Estradiol Levels Are Independent Predictors for Initiation of Anastrozole in Hypogonadal Men on Clomiphene Citrate

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          Abstract

          Purpose

          To assess the conversion rate from clomiphene citrate (CC) monotherapy to combination CC+anastrozole (AZ) therapy in hypogonadal men and the predictors associated with the initiation of AZ.

          Materials and Methods

          A retrospective review of records from hypogonadal men treated with CC in a single fertility center was performed from 2013 to 2018. Patient age, body mass index (BMI), blood pressure, and reproductive hormones were obtained at baseline. Obesity was defined as BMI≥30 kg/m 2. Cox proportional hazards models were used to identify predictors of switching to combination CC+AZ therapy.

          Results

          A total of 318 men on CC were included. Median (interquartile range) age was 34 years (30–39 years) and patients were followed for a median of 9 months (4–17 months). Of these, 97 (30.5%) were started on CC+AZ therapy. These patients had higher baseline BMI and estradiol, which in multivariable regression were significant predictors for switching to CC+AZ therapy. A threshold of 18.5 pg/mL for baseline estradiol provided the highest accuracy for predicting the addition of AZ after adjusting for baseline BMI and total testosterone levels.

          Conclusions

          In our practice, following CC monotherapy, 30% of men were initiated on CC+AZ. Obesity (BMI≥30 kg/m 2) and baseline estradiol ≥18.5 pg/mL can predict the conversion to combination therapy with addition of AZ. This information can be used to counsel patients and also help to identify patients who can be started on combination therapy upfront.

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          Most cited references20

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          Time-dependent ROC curves for censored survival data and a diagnostic marker.

          ROC curves are a popular method for displaying sensitivity and specificity of a continuous diagnostic marker, X, for a binary disease variable, D. However, many disease outcomes are time dependent, D(t), and ROC curves that vary as a function of time may be more appropriate. A common example of a time-dependent variable is vital status, where D(t) = 1 if a patient has died prior to time t and zero otherwise. We propose summarizing the discrimination potential of a marker X, measured at baseline (t = 0), by calculating ROC curves for cumulative disease or death incidence by time t, which we denote as ROC(t). A typical complexity with survival data is that observations may be censored. Two ROC curve estimators are proposed that can accommodate censored data. A simple estimator is based on using the Kaplan-Meier estimator for each possible subset X > c. However, this estimator does not guarantee the necessary condition that sensitivity and specificity are monotone in X. An alternative estimator that does guarantee monotonicity is based on a nearest neighbor estimator for the bivariate distribution function of (X, T), where T represents survival time (Akritas, M. J., 1994, Annals of Statistics 22, 1299-1327). We present an example where ROC(t) is used to compare a standard and a modified flow cytometry measurement for predicting survival after detection of breast cancer and an example where the ROC(t) curve displays the impact of modifying eligibility criteria for sample size and power in HIV prevention trials.
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            Evaluation and Management of Testosterone Deficiency: AUA Guideline

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              Hypogonadism and male obesity: Focus on unresolved questions

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                Author and article information

                Journal
                World J Mens Health
                World J Mens Health
                WJMH
                The World Journal of Men's Health
                Korean Society for Sexual Medicine and Andrology
                2287-4208
                2287-4690
                October 2020
                24 February 2020
                : 38
                : 4
                : 582-590
                Affiliations
                [1 ]Division of Urology, Department of Surgery, University of Utah School of Medicine, Salt Lake City, UT, USA.
                [2 ]Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA.
                Author notes
                Correspondence to: Sorena Keihani. Division of Urology, Department of Surgery, University of Utah School of Medicine, 30 North 1900 East, Salt Lake City, UT 84132, USA. Tel: +1-801-213-2700, Fax: +1-801-213-2700, sorena.keihani@ 123456hsc.utah.edu
                Author information
                https://orcid.org/0000-0001-9006-5809
                https://orcid.org/0000-0001-5326-9941
                https://orcid.org/0000-0002-4609-8344
                https://orcid.org/0000-0002-6292-276X
                https://orcid.org/0000-0002-6740-8348
                https://orcid.org/0000-0002-4401-4565
                Article
                10.5534/wjmh.190160
                7502320
                32202084
                5ce0421c-dce8-4c00-b3aa-aa91c90ca83a
                Copyright © 2020 Korean Society for Sexual Medicine and Andrology

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 06 December 2019
                : 02 January 2020
                : 29 January 2020
                Categories
                Original Article
                Hormonal Regulation of Male Reproduction and Hypogonadism

                anastrozole,clomiphene,hypogonadism,infertility, male,testosterone

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