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Articles by A. L Potosky
Total Records ( 2 ) for A. L Potosky
  B. B Reeve , A. L Potosky , A. W Smith , P. K Han , R. D Hays , W. W Davis , N. K Arora , S. C Haffer and S. B. Clauser

The impact of cancer on health-related quality of life (HRQOL) is poorly understood because of the lack of baseline HRQOL status before cancer diagnosis. To our knowledge, this is the first population-based study to quantify the nature and extent of HRQOL changes from before to after cancer diagnosis for nine types of cancer patients and to compare their health with individuals without cancer.


The Surveillance, Epidemiology, and End Results cancer registry data were linked with the Medicare Health Outcomes Survey (MHOS) data; data were collected from Medicare beneficiaries who were aged 65 years and older from 1998 through 2003. Cancer patients (n = 1432; with prostate, breast, colorectal, lung, bladder, endometrial, or kidney cancers; melanoma; or non-Hodgkin lymphoma [NHL]) were selected whose first cancer diagnosis occurred between their baseline and follow-up MHOS assessments. Control subjects without cancer (n = 7160) were matched to cancer patients by use of propensity scores that were estimated from demographics and comorbid medical conditions. Analysis of covariance models were used to estimate changes in HRQOL as assessed with the Medical Outcomes Study Short Form-36 survey (mean score = 50, SD = 10). All statistical tests were two-sided.


Patients with all cancer types (except melanoma and endometrial cancer) reported statistically significant declines in physical health (mean scores: prostate cancer = –3.4, 95% confidence interval [CI] = –2.5 to –4.2; breast cancer = –3.5, 95% CI = –2.5 to –4.5; bladder cancer = –4.3, 95% CI = –2.5 to –6.1; colorectal cancer = –4.4, 95% CI = –3.3 to –5.5; kidney cancer = –5.7, 95% CI = –3.2 to –8.2; NHL = –6.7, 95% CI = –4.4 to –9.1; and lung cancer = –7.5, 95% CI = –5.9 to –9.2) compared with the control subjects (mean score = –1.8, 95% CI = –1.6 to –2.0) (all P < .05). However, only lung (mean score = –5.4, 95% CI = –3.5 to –7.2), colorectal (mean score = –3.5, 95% CI = –2.2 to –4.7), and prostate (mean score = –2.8, 95% CI = –1.8 to –3.7) cancer patients showed statistically significant decreases in mental health relative to the mean change of the control subjects (mean score = –1.2, 95% CI = –0.9 to –1.4) (all P < .05).


These findings provide validation of the specific deleterious effects of cancer on HRQOL and an evidence base for future research and clinical interventions aimed at understanding and remediating these effects.

  A. N Freedman , L. B Sansbury , W. D Figg , A. L Potosky , S. R Weiss Smith , M. J Khoury , S. A Nelson , R. M Weinshilboum , M. J Ratain , H. L McLeod , R. S Epstein , G. S Ginsburg , R. L Schilsky , G Liu , D. A Flockhart , C. M Ulrich , R. L Davis , L. J Lesko , I Zineh , G Randhawa , C. B Ambrosone , M. V Relling , N Rothman , H Xie , M. R Spitz , R Ballard Barbash , J. H Doroshow and L. M. Minasian

Recent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individuals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a workshop titled "Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation" on July 21, 2009, in Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-based recommendations that were identified as a result of discussions held during this workshop. Key recommendations include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic research; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommendations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic and pharmacoepidemiologic information is translated into clinical practice.

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