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Non-iterative, regression-based estimation of haplotype associations with censored survival outcomes.

ABSTRACT: The general availability of reliable and affordable genotyping technology has enabled genetic association studies to move beyond small case-control studies to large prospective studies. For prospective studies, genetic information can be integrated into the analysis via haplotypes, with focus on their association with a censored survival outcome. We develop non-iterative, regression-based methods to estimate associations between common haplotypes and a censored survival outcome in large cohort studies. Our non-iterative methods--weighted estimation and weighted haplotype combination--are both based on the Cox regression model, but differ in how the imputed haplotypes are integrated into the model. Our approaches enable haplotype imputation to be performed once as a simple data-processing step, and thus avoid implementation based on sophisticated algorithms that iterate between haplotype imputation and risk estimation. We show that non-iterative weighted estimation and weighted haplotype combination provide valid tests for genetic associations and reliable estimates of moderate associations between common haplotypes and a censored survival outcome, and are straightforward to implement in standard statistical software. We apply the methods to an analysis of HSPB7-CLCNKA haplotypes and risk of adverse outcomes in a prospective cohort study of outpatients with chronic heart failure.

SUBMITTER: French B

PROVIDER: S-EPMC3395231 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Non-iterative, regression-based estimation of haplotype associations with censored survival outcomes.

French Benjamin B Lumley Thomas T Cappola Thomas P TP Mitra Nandita N

Statistical applications in genetics and molecular biology 20120215 3

The general availability of reliable and affordable genotyping technology has enabled genetic association studies to move beyond small case-control studies to large prospective studies. For prospective studies, genetic information can be integrated into the analysis via haplotypes, with focus on their association with a censored survival outcome. We develop non-iterative, regression-based methods to estimate associations between common haplotypes and a censored survival outcome in large cohort s ...[more]

PMID: 22499703

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Project description:BackgroundThe analysis of disease-free survival and related factors leads to a better understanding of the patient's condition and recurrence-related characteristics and provides a basis for more appropriate treatment guidance. In this study, we aimed to investigate the role of prognostic factors on disease-free survival in breast cancer with a quantile regression model.MethodsThis retrospective study was conducted by reviewing data obtained from 2056 breast cancer patients. Age at diagnosis and education status, tumor size, lymph node ratio, tumor grade, estrogen receptor and progesterone receptor, type of surgery, use of radiotherapy, chemotherapy, and hormone therapy were the prognosis factors considered in this study. A quantile regression model was used to investigate prognostic factors of disease-free survival in breast cancer.ResultsDisease recurrence was verified in 251 (13.9%) women, and 39 (0.02%) women died before experience recurrence. The 10th percentile of disease-free survival for patients with the hormone therapy was 23.85 months greater than patients who did not receive this treatment (P value < .001). In the examination of the tumor size, the 10th and 20th percentiles of disease-free survival for patients with tumor size > 5 cm were 31.06 and 27 months less than patients with the tumor size < 2 cm, respectively (P value = .006 and .021, respectively). Compared with grade 1 tumors, the 10th and 20th percentiles of disease-free survival for patients with grade 3 tumors decreased 30.11 and 38.32 months, respectively (P value < .001 and .038, respectively). The 10th and 20th percentiles of disease-free survival decreased 28.16 and 45.32 months with a 1 unit increase in lymph node ratio, respectively (P value = .032 and .032, respectively).ConclusionsAmong the prognostic factors, tumor size, grade, and lymph node ratio showed a close relationship with disease-free survival in breast cancer. The findings indicated that developing public screening and educational programs through the health care system with more emphasis on low-educated women is needed among Iranian women.

Dataset Information

Non-iterative, regression-based estimation of haplotype associations with censored survival outcomes.

Publications

Non-iterative, regression-based estimation of haplotype associations with censored survival outcomes.

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