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10.1186/s12982-017-0060-8 http://scihub22266oqcxt.onion/10.1186/s12982-017-0060-8 C5460539!5460539!28592984     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28592984&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Emerg+Themes+Epidemiol 2017 ; 14 (ä): ä Nephropedia Template TP {{tp|p=28592984|t=2017. On hazard ratio estimators by proportional hazards models in matched-pair cohort studies |pdf=|usr=}}{{28592984}} gab.com Text On hazard ratio estimators by proportional hazards models in matched-pair cohort studies JO: Emerg Themes Epidemiol http://www.kidney.de/pget.php?&tw=1&pmid=28592984 #FOAvip Background: In matched-pair cohort studies with censored events, the hazard ratio (HR) may be of main interest. However, it is lesser known in epidemiologic literature that the partial maximum likelihood estimator of a common HR conditional on matched pairs is written in a simple form, namely, the ratio of the numbers of two pair-types. Moreover, because HR is a noncollapsible measure and its constancy across matched pairs is a restrictive assumption, marginal HR as ?average? HR may be targeted more than conditional HR in analysis. Methods: Based on its simple expression, we provided an alternative interpretation of the common HR estimator as the odds of the matched-pair analog of C-statistic for censored time-to-event data. Through simulations assuming proportional hazards within matched pairs, the influence of various censoring patterns on the marginal and common HR estimators of unstratified and stratified proportional hazards models, respectively, was evaluated. The methods were applied to a real propensity-score matched dataset from the Rotterdam tumor bank of primary breast cancer. Results: We showed that stratified models unbiasedly estimated a common HR under the proportional hazards within matched pairs. However, the marginal HR estimator with robust variance estimator lacks interpretation as an ?average? marginal HR even if censoring is unconditionally independent to event, unless no censoring occurs or no exposure effect is present. Furthermore, the exposure-dependent censoring biased the marginal HR estimator away from both conditional HR and an ?average? marginal HR irrespective of whether exposure effect is present. From the matched Rotterdam dataset, we estimated HR for relapse-free survival of absence versus presence of chemotherapy; estimates (95% confidence interval) were 1.47 (1.18?1.83) for common HR and 1.33 (1.13?1.57) for marginal HR. Conclusion: The simple expression of the common HR estimator would be a useful summary of exposure effect, which is less sensitive to censoring patterns than the marginal HR estimator. The common and the marginal HR estimators, both relying on distinct assumptions and interpretations, are complementary alternatives for each other. Electronic supplementary material: The online version of this article (doi:10.1186/s12982-017-0060-8) contains supplementary material, which is available to authorized users. Twit Text FOAVip On hazard ratio estimators by proportional hazards models in matched-pair cohort studies ????Emerg Themes Epidemiol http://www.kidney.de/pget.php?&tw=1&pmid=28592984 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28592984 #FOAvip English Wikipedia <ref>{{Cite pmid|28592984}}</ref> On hazard ratio estimators by proportional hazards models in matched-pair cohort studies #MMPMID28592984 Shinozaki T; Mansournia MA; Matsuyama Y Emerg Themes Epidemiol 2017[]; 14 (ä): ä PMID28592984show ga Background: In matched-pair cohort studies with censored events, the hazard ratio (HR) may be of main interest. However, it is lesser known in epidemiologic literature that the partial maximum likelihood estimator of a common HR conditional on matched pairs is written in a simple form, namely, the ratio of the numbers of two pair-types. Moreover, because HR is a noncollapsible measure and its constancy across matched pairs is a restrictive assumption, marginal HR as ?average? HR may be targeted more than conditional HR in analysis. Methods: Based on its simple expression, we provided an alternative interpretation of the common HR estimator as the odds of the matched-pair analog of C-statistic for censored time-to-event data. Through simulations assuming proportional hazards within matched pairs, the influence of various censoring patterns on the marginal and common HR estimators of unstratified and stratified proportional hazards models, respectively, was evaluated. The methods were applied to a real propensity-score matched dataset from the Rotterdam tumor bank of primary breast cancer. Results: We showed that stratified models unbiasedly estimated a common HR under the proportional hazards within matched pairs. However, the marginal HR estimator with robust variance estimator lacks interpretation as an ?average? marginal HR even if censoring is unconditionally independent to event, unless no censoring occurs or no exposure effect is present. Furthermore, the exposure-dependent censoring biased the marginal HR estimator away from both conditional HR and an ?average? marginal HR irrespective of whether exposure effect is present. From the matched Rotterdam dataset, we estimated HR for relapse-free survival of absence versus presence of chemotherapy; estimates (95% confidence interval) were 1.47 (1.18?1.83) for common HR and 1.33 (1.13?1.57) for marginal HR. Conclusion: The simple expression of the common HR estimator would be a useful summary of exposure effect, which is less sensitive to censoring patterns than the marginal HR estimator. The common and the marginal HR estimators, both relying on distinct assumptions and interpretations, are complementary alternatives for each other. Electronic supplementary material: The online version of this article (doi:10.1186/s12982-017-0060-8) contains supplementary material, which is available to authorized users. äOn hazard ratio estimators by proportional hazards models in matched-p(epmc).pdf DeepDyve Pubget Overpricing