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Data mining identifies Digit Symbol Substitution Test score and serum cystatin C as dominant predictors of mortality in older men and women.

ABSTRACT: Characterization of long-term health trajectory in older individuals is important for proactive health management. However, the relative prognostic value of information contained in clinical profiles of nonfrail older adults is often unclear.We screened 825 phenotypic and genetic measures evaluated during the Health, Aging, and Body Composition Study (Health ABC) baseline visit (3,067 men and women aged 70-79). Variables that best predicted mortality over 13 years of follow-up were identified using 10-fold cross-validation.Mortality was most strongly associated with low Digit Symbol Substitution Test (DSST) score (DSST<25; 21.9% of cohort; hazard ratio [HR]=1.87±0.06) and elevated serum cystatin C (?1.30?mg/mL; 12.1% of cohort; HR=2.25±0.07). These variables predicted mortality better than 823 other measures, including baseline age and a 45-variable health deficit index. Given elevated cystatin C (?1.30?mg/mL), mortality risk was further increased by high serum creatinine, high abdominal visceral fat density, and smoking history (2.52?HR ?3.73). Given a low DSST score (<25) combined with low-to-moderate cystatin C (<1.30?mg/mL), mortality risk was highest among those with elevated plasma resistin and smoking history (1.90?HR?2.02).DSST score and serum cystatin C warrant priority consideration for the evaluation of mortality risk in older individuals. Both variables, taken individually, predict mortality better than chronological age or a health deficit index in well-functioning older adults (ages 70-79). DSST score and serum cystatin C can thus provide evidence-based tools for geriatric assessment.

SUBMITTER: Swindell WR

PROVIDER: S-EPMC3419847 | biostudies-other | 2012 Aug

REPOSITORIES: biostudies-other

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Data mining identifies Digit Symbol Substitution Test score and serum cystatin C as dominant predictors of mortality in older men and women.

Swindell William R WR Cummings Steven R SR Sanders Jason L JL Caserotti Paolo P Rosano Caterina C Rosano Caterina C Satterfield Suzanne S Strotmeyer Elsa S ES Harris Tamara B TB Simonsick Eleanor M EM Cawthon Peggy M PM

Rejuvenation research 20120518 4

<h4>Background</h4>Characterization of long-term health trajectory in older individuals is important for proactive health management. However, the relative prognostic value of information contained in clinical profiles of nonfrail older adults is often unclear.<h4>Methods</h4>We screened 825 phenotypic and genetic measures evaluated during the Health, Aging, and Body Composition Study (Health ABC) baseline visit (3,067 men and women aged 70-79). Variables that best predicted mortality over 13 ye ...[more]

PMID: 22607624

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Project description:BACKGROUND:Patients with newly diagnosed non-metastatic prostate adenocarcinoma are typically classified as at low, intermediate, or high risk of disease progression using blood prostate-specific antigen concentration, tumour T category, and tumour pathological Gleason score. Classification is used to both predict clinical outcome and to inform initial management. However, significant heterogeneity is observed in outcome, particularly within the intermediate risk group, and there is an urgent need for additional markers to more accurately hone risk prediction. Recently developed web-based visualization and analysis tools have facilitated rapid interrogation of large transcriptome datasets, and querying broadly across multiple large datasets should identify predictors that are widely applicable. METHODS:We used camcAPP, cBioPortal, CRN, and NIH NCI GDC Data Portal to data mine publicly available large prostate cancer datasets. A test set of biomarkers was developed by identifying transcripts that had: 1) altered abundance in prostate cancer, 2) altered expression in patients with Gleason score 7 tumours and biochemical recurrence, 3) correlation of expression with time until biochemical recurrence across three datasets (Cambridge, Stockholm, MSKCC). Transcripts that met these criteria were then examined in a validation dataset (TCGA-PRAD) using univariate and multivariable models to predict biochemical recurrence in patients with Gleason score 7 tumours. RESULTS:Twenty transcripts met the test criteria, and 12 were validated in TCGA-PRAD Gleason score 7 patients. Ten of these transcripts remained prognostic in Gleason score 3?+?4?=?7, a sub-group of Gleason score 7 patients typically considered at a lower risk for poor outcome and often not targeted for aggressive management. All transcripts positively associated with recurrence encode or regulate mitosis and cell cycle-related proteins. The top performer was BUB1, one of four key MIR145-3P microRNA targets upregulated in hormone-sensitive as well as castration-resistant PCa. SRD5A2 converts testosterone to its more active form and was negatively associated with biochemical recurrence. CONCLUSIONS:Unbiased mining of large patient datasets identified 12 transcripts that independently predicted disease recurrence risk in Gleason score 7 prostate cancer. The mitosis and cell cycle proteins identified are also implicated in progression to castration-resistant prostate cancer, revealing a pivotal role for loss of cell cycle control in the latter.

Dataset Information

Data mining identifies Digit Symbol Substitution Test score and serum cystatin C as dominant predictors of mortality in older men and women.

Publications

Data mining identifies Digit Symbol Substitution Test score and serum cystatin C as dominant predictors of mortality in older men and women.

Similar Datasets

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