Literature DB >> 12543625

Multiple informants: a new method to assess breast cancer patients' comorbidity.

Timothy L Lash1, Soe Soe Thwin, Nicholas J Horton, Edward Guadagnoli, Rebecca A Silliman.   

Abstract

Past assessments of comorbidity indices have sought to recommend a single index that performs better than others. The authors used a multiple informants approach as an alternative method to simultaneously assess five indices of comorbidity. This approach provides a single estimate of the overall effect of comorbidity and evaluates the relation any individual index has to the outcomes of interest. Association of comorbidity with definitive primary therapy, discussion of tamoxifen, and receipt of tamoxifen was evaluated in a cohort of 830 older breast cancer patients enrolled at four geographically distinct centers in the United States from 1996 to 1999. The estimated adjusted effect of a unit increase in comorbidity on the odds of discussing tamoxifen therapy was 0.70 (95% confidence interval: 0.56, 0.88). An increase in comorbidity was not associated with receipt of definitive primary therapy (odds ratio = 0.94, 95% confidence interval: 0.79, 1.13) or receipt of tamoxifen (odds ratio = 0.96, 95% confidence interval: 0.72, 1.27). The multiple informants regression proved superior to separate regression models that included only one index. In analyses that require comorbidity adjustment and for which no single index is expected to be ideal, the multiple informants approach is an attractive alternative to selecting a single index and to other methods of using multiple indices.

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Year:  2003        PMID: 12543625     DOI: 10.1093/aje/kwf193

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  17 in total

Review 1.  Methodology, design, and analytic techniques to address measurement of comorbid disease.

Authors:  Timothy L Lash; Vincent Mor; Darryl Wieland; Luigi Ferrucci; William Satariano; Rebecca A Silliman
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2007-03       Impact factor: 6.053

2.  Analyzing multiple informant data from an evaluation of the health disparities collaboratives.

Authors:  A James O'Malley; Bruce E Landon; Edward Guadagnoli
Journal:  Health Serv Res       Date:  2007-02       Impact factor: 3.402

3.  Association of patient-centered outcomes with patient-reported and ICD-9-based morbidity measures.

Authors:  Elizabeth A Bayliss; Jennifer L Ellis; Jo Ann Shoup; Chan Zeng; Deanna B McQuillan; John F Steiner
Journal:  Ann Fam Med       Date:  2012 Mar-Apr       Impact factor: 5.166

4.  A 50% higher prevalence of life-shortening chronic conditions among cancer patients with low socioeconomic status.

Authors:  W J Louwman; M J Aarts; S Houterman; F J van Lenthe; J W W Coebergh; M L G Janssen-Heijnen
Journal:  Br J Cancer       Date:  2010-10-26       Impact factor: 7.640

5.  Effect of comorbidity on the treatment and prognosis of elderly patients with non-small cell lung cancer.

Authors:  M L G Janssen-Heijnen; S Smulders; V E P P Lemmens; F W J M Smeenk; H J A A van Geffen; J W W Coebergh
Journal:  Thorax       Date:  2004-07       Impact factor: 9.139

6.  The impact of comorbidity on the survival of postmenopausal women with breast cancer.

Authors:  G Nagel; U Wedding; B Röhrig; D Katenkamp
Journal:  J Cancer Res Clin Oncol       Date:  2004-11       Impact factor: 4.553

Review 7.  Some old and some new statistical tools for outcomes research.

Authors:  Sharon-Lise T Normand
Journal:  Circulation       Date:  2008-08-19       Impact factor: 29.690

8.  Seniors' self-reported multimorbidity captured biopsychosocial factors not incorporated into two other data-based morbidity measures.

Authors:  Elizabeth A Bayliss; Jennifer L Ellis; John F Steiner
Journal:  J Clin Epidemiol       Date:  2008-08-30       Impact factor: 6.437

9.  The role of comorbidity assessment in guiding treatment decision-making for women with early breast cancer: a systematic literature review.

Authors:  Stephanie Webster; Sharon Lawn; Raymond Chan; Bogda Koczwara
Journal:  Support Care Cancer       Date:  2019-12-11       Impact factor: 3.603

10.  Quality-of-life: A study on patients of carcinoma breast and its pitfalls in Indian society.

Authors:  A K Shah; L S Vohra
Journal:  Indian J Surg       Date:  2010-07-01       Impact factor: 0.656

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