Dataset Information

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

ABSTRACT: BACKGROUND:Given the growing interest in the cancer burden in persons living with HIV/AIDS, we examined the validity of data sources for cancer diagnoses (cancer registry versus International Classification of Diseases, Ninth Revision [ICD-9 codes]) and compared the association between HIV status and cancer risk using each data source in the Veterans Aging Cohort Study (VACS), a prospective cohort of HIV-infected and uninfected veterans from 1996 to 2008. METHODS:We reviewed charts to confirm potential incident cancers at four VACS sites. In the entire cohort, we calculated cancer-type-specific age-, sex-, race/ethnicity-, and calendar-period-standardized incidence rates and incidence rate ratios (IRR) (HIV-infected versus uninfected). We calculated standardized incidence ratios (SIR) to compare VACS and Surveillance, Epidemiology, and End Results rates. RESULTS:Compared to chart review, both Veterans Affairs Central Cancer Registry (VACCR) and ICD-9 diagnoses had approximately 90% sensitivity; however, VACCR had higher positive predictive value (96% versus 63%). There were 6,010 VACCR and 13,386 ICD-9 incident cancers among 116,072 veterans. Although ICD-9 rates tended to be double VACCR rates, most IRRs were in the same direction and of similar magnitude, regardless of data source. Using either source, all cancers combined, most viral-infection-related cancers, lung cancer, melanoma, and leukemia had significantly elevated IRRs. Using ICD-9, eight additional IRRs were significantly elevated, most likely due to false positive diagnoses. Most ICD-9 SIRs were significantly elevated and all were higher than the corresponding VACCR SIR. CONCLUSIONS:ICD-9 may be used with caution for estimating IRRs, but should be avoided when estimating incidence or SIRs. Elevated cancer risk based on VACCR diagnoses among HIV-infected veterans was consistent with other studies.

SUBMITTER: Park LS

PROVIDER: S-EPMC4285627 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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

Park Lesley S LS Tate Janet P JP Rodriguez-Barradas Maria C MC Rimland David D Goetz Matthew Bidwell MB Gibert Cynthia C Brown Sheldon T ST Kelley Michael J MJ Justice Amy C AC Dubrow Robert R

Journal of AIDS & clinical research 20140701 7

<h4>Background</h4>Given the growing interest in the cancer burden in persons living with HIV/AIDS, we examined the validity of data sources for cancer diagnoses (cancer registry versus International Classification of Diseases, Ninth Revision [ICD-9 codes]) and compared the association between HIV status and cancer risk using each data source in the Veterans Aging Cohort Study (VACS), a prospective cohort of HIV-infected and uninfected veterans from 1996 to 2008.<h4>Methods</h4>We reviewed chart ...[more]

PMID: 25580366

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Project description:Human immunodeficiency virus (HIV)-infected (HIV+) patients on combination antiretroviral therapy are living longer but have increased risk for aging-associated disease which may lead to increasing critical care requirements. We compare medical ICU admission characteristics and outcomes among HIV infected and demographically similar uninfected patients (uninfected) and considered whether an index which combines routine clinical biomarkers (the Veterans Aging Cohort Study Index) predicts 30-day medical ICU mortality.Observational data analyses (Veterans Aging Cohort Study).Eight Veterans Affairs medical centers nationwide.HIV infected and uninfected with a medical ICU admission between 2002 and 2010.None.Medical ICU admission was determined using bedsection (Veterans Affairs) and revenue center codes (Medicare). For Veterans Affairs admissions, we used clinical data to calculate Veterans Aging Cohort Study Index scores and multivariable logistic regression to determine factors associated with 30-day mortality. Overall, 539 of 3,620 (15%) HIV infected and 375 of 3,639 (10%) uninfected had a medical ICU admission; 72% and 78%, respectively, were Veterans Affairs based. HIV+ patients were younger at admission (p < 0.0001). Although most HIV+ patients were on antiretroviral therapy (71%) with undetectable HIV-1 RNA (54%), compared with uninfected they were more commonly admitted with respiratory diagnoses or infections (21% vs. 12%), were more likely to require mechanical ventilation (17% vs. 9%; p = 0.001), and had a higher mortality rate (18.6% vs. 11.2%, p = 0.003). Cardiovascular diagnoses were less common among HIV infected (18% vs. 29%; p < 0.0001). In logistic regression (c-statistic 0.87), a 5-point increment in Veterans Aging Cohort Study Index was associated with an odds ratio of death of 1.22 (95% confidence interval 1.14-1.30) among HIV infected and of 1.50 (95% confidence interval 1.29-1.76) among uninfected; infection/sepsis and respiratory diagnoses were also associated with mortality.Medical ICU admission was frequent, 30-day mortality higher, and mechanical ventilation more common in HIV infected compared with uninfected. The Veterans Aging Cohort Study Index calculated at medical ICU admission predicted 30-day mortality for HIV infected and uninfected. As more individuals age with HIV, their requirements for medical ICU care may be greater than demographically similar uninfected individuals.

Project description:Electronic health records (EHR) provide a comprehensive resource for discovery, allowing unprecedented exploration of the impact of genetic architecture on health and disease. The data of EHRs also allow for exploration of the complex interactions between health measures across health and disease. The discoveries arising from EHR based research provide important information for the identification of genetic variation for clinical decision-making. Due to the breadth of information collected within the EHR, a challenge for discovery using EHR based data is the development of high-throughput tools that expose important areas of further research, from genetic variants to phenotypes. Phenome-Wide Association studies (PheWAS) provide a way to explore the association between genetic variants and comprehensive phenotypic measurements, generating new hypotheses and also exposing the complex relationships between genetic architecture and outcomes, including pleiotropy. EHR based PheWAS have mainly evaluated associations with case/control status from International Classification of Disease, Ninth Edition (ICD-9) codes. While these studies have highlighted discovery through PheWAS, the rich resource of clinical lab measures collected within the EHR can be better utilized for high-throughput PheWAS analyses and discovery. To better use these resources and enrich PheWAS association results we have developed a sound methodology for extracting a wide range of clinical lab measures from EHR data. We have extracted a first set of 21 clinical lab measures from the de-identified EHR of participants of the Geisinger MyCodeTM biorepository, and calculated the median of these lab measures for 12,039 subjects. Next we evaluated the association between these 21 clinical lab median values and 635,525 genetic variants, performing a genome-wide association study (GWAS) for each of 21 clinical lab measures. We then calculated the association between SNPs from these GWAS passing our Bonferroni defined p-value cutoff and 165 ICD-9 codes. Through the GWAS we found a series of results replicating known associations, and also some potentially novel associations with less studied clinical lab measures. We found the majority of the PheWAS ICD-9 diagnoses highly related to the clinical lab measures associated with same SNPs. Moving forward, we will be evaluating further phenotypes and expanding the methodology for successful extraction of clinical lab measurements for research and PheWAS use. These developments are important for expanding the PheWAS approach for improved EHR based discovery.

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Dataset Information

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

Publications

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

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