Literature DB >> 15970786

The added value of claims for cancer surveillance: results of varying case definitions.

Lynne Penberthy1, Donna McClish, Claudine Manning, Sheldon Retchin, Tom Smith.   

Abstract

OBJECTIVE: As cancer diagnosis and treatment has moved to the outpatient healthcare setting, traditional cancer surveillance tools are less effective for complete and unbiased capture of incident cases. This study evaluates the potential for Medicare data to supplement cancer surveillance in a unique manner by using a standard that is independent of a central cancer registry.
DESIGN: State cancer registry records were matched with Medicare data. Case validation included inpatient record abstraction combined with a mail/telephone survey of treating physicians. The positive predictive value (PPV), sensitivity (capture rate), and potential additional cases were calculated for 6 Medicare claims-based case definitions.
RESULTS: The PPV varied according to cancer site and definition, ranging from 70%-97% (prostate) to 87%-98% (breast). Sensitivity varied inversely with PPV, ranging from 51%-94% (breast) to 10%-88% (lung). The most important factors that predicted being missed by the registry were having no admission to an ACOS-certified hospital and no surgical treatment.
CONCLUSION: Medicare data represent a valid resource for supplementing state cancer registries in surveillance efforts. This potential is especially applicable to cancers predominantly diagnosed and treated outside the hospital setting.

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Mesh:

Year:  2005        PMID: 15970786     DOI: 10.1097/01.mlr.0000167176.41645.c7

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  16 in total

1.  Cancer Incidence in HIV-Infected Versus Uninfected Veterans: Comparison of Cancer Registry and ICD-9 Code Diagnoses.

Authors:  Lesley S Park; Janet P Tate; Maria C Rodriguez-Barradas; David Rimland; Matthew Bidwell Goetz; Cynthia Gibert; Sheldon T Brown; Michael J Kelley; Amy C Justice; Robert Dubrow
Journal:  J AIDS Clin Res       Date:  2014-07

2.  Confirmation of family cancer history reported in a population-based survey.

Authors:  Phuong L Mai; Anne O Garceau; Barry I Graubard; Marsha Dunn; Timothy S McNeel; Lou Gonsalves; Mitchell H Gail; Mark H Greene; Gordon B Willis; Louise Wideroff
Journal:  J Natl Cancer Inst       Date:  2011-05-11       Impact factor: 13.506

3.  Predictors of colorectal cancer following a negative colonoscopy in the Medicare population.

Authors:  Amanpal Singh; Yong-Fang Kuo; Taylor S Riall; G S Raju; James S Goodwin
Journal:  Dig Dis Sci       Date:  2011-06-17       Impact factor: 3.199

4.  Tradeoffs between accuracy measures for electronic health care data algorithms.

Authors:  Jessica Chubak; Gaia Pocobelli; Noel S Weiss
Journal:  J Clin Epidemiol       Date:  2011-12-23       Impact factor: 6.437

5.  Bone Morphogenetic Protein Use and Cancer Risk Among Patients Undergoing Lumbar Arthrodesis: A Case-Cohort Study Using the SEER-Medicare Database.

Authors:  Daniel C Beachler; Elizabeth L Yanik; Brook I Martin; Ruth M Pfeiffer; Sohail K Mirza; Richard A Deyo; Eric A Engels
Journal:  J Bone Joint Surg Am       Date:  2016-07-06       Impact factor: 5.284

6.  Risk of colorectal cancer in men on long-term androgen deprivation therapy for prostate cancer.

Authors:  Silke Gillessen; Arnoud Templeton; Giancarlo Marra; Yong-Fang Kuo; Emanuele Valtorta; Vahakn B Shahinian
Journal:  J Natl Cancer Inst       Date:  2010-11-10       Impact factor: 13.506

7.  Capitalizing on Central Registries for Expanded Cancer Surveillance and Research.

Authors:  Cathy J Bradley; Julia Entwistle; Lindsay M Sabik; Richard C Lindrooth; Marcelo Perraillon
Journal:  Med Care       Date:  2022-02-01       Impact factor: 2.983

8.  Barriers to therapeutic clinical trials enrollment: differences between African-American and white cancer patients identified at the time of eligibility assessment.

Authors:  Lynne Penberthy; Richard Brown; Maureen Wilson-Genderson; Bassam Dahman; Gordon Ginder; Laura A Siminoff
Journal:  Clin Trials       Date:  2012-10-02       Impact factor: 2.486

9.  Treatment patterns for prostate cancer: comparison of Medicare claims data to medical record review.

Authors:  Steven T Fleming; Ann S Hamilton; Susan A Sabatino; Gretchen G Kimmick; Xiao-Cheng Wu; Jean B Owen; Bin Huang; Wenke Hwang
Journal:  Med Care       Date:  2014-09       Impact factor: 2.983

10.  Evaluation of three algorithms to identify incident breast cancer in Medicare claims data.

Authors:  Heather T Gold; Huong T Do
Journal:  Health Serv Res       Date:  2007-10       Impact factor: 3.402

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