Literature DB >> 26172862

Negative Control Outcomes and the Analysis of Standardized Mortality Ratios.

David B Richardson1, Alexander P Keil, Eric Tchetgen Tchetgen, Glinda Cooper.   

Abstract

In occupational cohort mortality studies, epidemiologists often compare the observed number of deaths in the cohort to the expected number obtained by multiplying person-time accrued in the study cohort by the mortality rate in an external reference population. Interpretation of the result may be difficult due to noncomparability of the occupational cohort and reference population with respect to unmeasured risk factors for the outcome of interest. We describe an approach to estimate an adjusted standardized mortality ratio (aSMR) to control for such bias. The approach draws on methods developed for the use of negative control outcomes. Conditions necessary for unbiased estimation are described, as well as looser conditions necessary for bias reduction. The approach is illustrated using data on bladder cancer mortality among male Oak Ridge National Laboratory workers. The SMR for bladder cancer was elevated among hourly-paid males (SMR = 1.9; 95% confidence interval [CI] = 1.3, 2.7) but not among monthly-paid males (SMR = 1.0; 95% CI = 0.67, 1.3). After indirect adjustment using the proposed approach, the mortality ratios were similar in magnitude among hourly- and monthly-paid men (aSMR = 2.2; 95% CI = 1.5, 3.2; and, aSMR = 2.0; 95% CI = 1.4, 2.8, respectively). The proposed adjusted SMR offers a complement to typical SMR analyses.

Entities:  

Mesh:

Year:  2015        PMID: 26172862      PMCID: PMC4763995          DOI: 10.1097/EDE.0000000000000353

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  14 in total

1.  Estimating causal effects.

Authors:  George Maldonado; Sander Greenland
Journal:  Int J Epidemiol       Date:  2002-04       Impact factor: 7.196

2.  New developments in the Life Table Analysis System of the National Institute for Occupational Safety and Health.

Authors:  K Steenland; J Beaumont; S Spaeth; D Brown; A Okun; L Jurcenko; B Ryan; S Phillips; R Roscoe; L Stayner
Journal:  J Occup Med       Date:  1990-11

3.  Update of the NIOSH life table analysis system: a person-years analysis program for the windows computing environment.

Authors:  Mary K Schubauer-Berigan; Misty J Hein; William M Raudabaugh; Avima M Ruder; Sharon R Silver; Steven Spaeth; Kyle Steenland; Martin R Petersen; Kathleen M Waters
Journal:  Am J Ind Med       Date:  2011-08-30       Impact factor: 2.214

4.  Regression modelling and other methods to control confounding.

Authors:  R McNamee
Journal:  Occup Environ Med       Date:  2005-07       Impact factor: 4.402

5.  Tenth revision U.S. mortality rates for use with the NIOSH Life Table Analysis System.

Authors:  Cynthia F Robinson; Teresa M Schnorr; Rick T Cassinelli; Geoffrey M Calvert; N Kyle Steenland; Christine M Gersic; Mary K Schubauer-Berigan
Journal:  J Occup Environ Med       Date:  2006-07       Impact factor: 2.162

6.  Assessment and indirect adjustment for confounding by smoking in cohort studies using relative hazards models.

Authors:  David B Richardson; Dominique Laurier; Mary K Schubauer-Berigan; Eric Tchetgen Tchetgen; Stephen R Cole
Journal:  Am J Epidemiol       Date:  2014-09-21       Impact factor: 4.897

7.  Mortality odds ratio, proportionate mortality ratio, and healthy worker effect.

Authors:  W Stewart; K Hunting
Journal:  Am J Ind Med       Date:  1988       Impact factor: 2.214

8.  The mortality odds ratio (MOR) in occupational mortality studies--selection of reference occupation(s) and reference cause(s) of death.

Authors:  J D Wang; O S Miettinen
Journal:  Ann Acad Med Singapore       Date:  1984-04       Impact factor: 2.473

9.  An alternative to the proportionate mortality ratio.

Authors:  O S Miettinen; J D Wang
Journal:  Am J Epidemiol       Date:  1981-07       Impact factor: 4.897

10.  The control outcome calibration approach for causal inference with unobserved confounding.

Authors:  Eric Tchetgen Tchetgen
Journal:  Am J Epidemiol       Date:  2013-12-20       Impact factor: 4.897

View more
  10 in total

1.  The Authors Respond.

Authors:  David B Richardson; Alexander P Keil; Eric J Tchetgen Tchetgen; Glinda S Cooper
Journal:  Epidemiology       Date:  2017-05       Impact factor: 4.822

2.  Observed and Expected Mortality in Cohort Studies.

Authors:  David B Richardson; Alexander P Keil; Stephen R Cole; Richard F MacLehose
Journal:  Am J Epidemiol       Date:  2017-03-15       Impact factor: 4.897

3.  Observational studies and the difficult quest for causality: lessons from vaccine effectiveness and impact studies.

Authors:  Marc Lipsitch; Ayan Jha; Lone Simonsen
Journal:  Int J Epidemiol       Date:  2016-12-01       Impact factor: 7.196

4.  Overall and cause-specific mortality in a cohort of farmers and their spouses.

Authors:  Srishti Shrestha; Christine G Parks; Alexander P Keil; David M Umbach; Catherine C Lerro; Charles F Lynch; Honglei Chen; Aaron Blair; Stella Koutros; Jonathan N Hofmann; Laura E Beane Freeman; Dale P Sandler
Journal:  Occup Environ Med       Date:  2019-09       Impact factor: 4.402

5.  Cancer and noncancer mortality among aluminum smelting workers in Badin, North Carolina.

Authors:  Elizabeth S McClure; Pavithra Vasudevan; Nathan DeBono; Whitney R Robinson; Stephen W Marshall; David Richardson
Journal:  Am J Ind Med       Date:  2020-07-10       Impact factor: 2.214

6.  A Selective Review of Negative Control Methods in Epidemiology.

Authors:  Xu Shi; Wang Miao; Eric Tchetgen Tchetgen
Journal:  Curr Epidemiol Rep       Date:  2020-10-15

7.  The predictive performance of SAPS 2 and SAPS 3 in an intermediate care unit for internal medicine at a German university transplant center; A retrospective analysis.

Authors:  Michael Jahn; Jan Rekowski; Guido Gerken; Andreas Kribben; Ali Canbay; Antonios Katsounas
Journal:  PLoS One       Date:  2019-09-25       Impact factor: 3.240

8.  Air Pollution, housing and respirfatory tract Infections in Children: NatIonal birth Cohort study (PICNIC): study protocol.

Authors:  Graziella Favarato; Tom Clemens; Steven Cunningham; Chris Dibben; Alison Macfarlane; Ai Milojevic; Jonathon Taylor; Linda Petronella Martina Maria Wijlaars; Rachael Wood; Pia Hardelid
Journal:  BMJ Open       Date:  2021-05-03       Impact factor: 2.692

9.  Cancer and non-cancer mortality among French uranium cycle workers: the TRACY cohort.

Authors:  Eric Samson; Irwin Piot; Sergey Zhivin; David B Richardson; Pierre Laroche; Ana-Paula Serond; Dominique Laurier; Olivier Laurent
Journal:  BMJ Open       Date:  2016-04-05       Impact factor: 2.692

10.  Brief Report: Negative Controls to Detect Selection Bias and Measurement Bias in Epidemiologic Studies.

Authors:  Benjamin F Arnold; Ayse Ercumen; Jade Benjamin-Chung; John M Colford
Journal:  Epidemiology       Date:  2016-09       Impact factor: 4.822

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.