Recurrent Osteosarcoma Clinical Trial
Official title:
Retrospective Study of Genetic Risk Factors for Osteosarcoma
Verified date | May 2016 |
Source | Children's Oncology Group |
Contact | n/a |
Is FDA regulated | No |
Health authority | United States: Institutional Review Board |
Study type | Observational |
This research trial studies blood samples from patients with osteosarcoma. Studying the genes found in samples of blood from patients with osteosarcoma may help doctors identify biomarkers related to the disease.
Status | Completed |
Enrollment | 1000 |
Est. completion date | |
Est. primary completion date | May 2016 |
Accepts healthy volunteers | No |
Gender | Both |
Age group | N/A and older |
Eligibility |
Inclusion Criteria: - Blood samples collected from clinical trials COG-P9851 and COG-AOST06B1 |
Observational Model: Case Control, Time Perspective: Retrospective
Country | Name | City | State |
---|---|---|---|
United States | Children's Oncology Group | Arcadia | California |
Lead Sponsor | Collaborator |
---|---|
Children's Oncology Group | National Cancer Institute (NCI) |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Hardy-Weinberg equilibrium on all SNPs | Determined on all SNPs by chi-square tests. | Baseline | No |
Primary | SNPs associated with OS | Logistic regression will be used to estimate odds ratios and 95% confidence intervals for the association between each SNP and OS under co-dominant, dominant and recessive genetic models. Stratified analyses will be conducted to examine sex, tumor subtype and outcome differences. | Baseline | No |
Primary | Gene-gene interactions | Assessed using a multiplicative model. Haplotypes will be constructed using both Bayesian and expectation-maximization algorithms. Differences between cases and controls will be evaluated with HaploStats which uses haplotype posterior probabilities as weights to update the regression coefficients in an iterative manner. | Baseline | No |
Primary | Survival outcomes | Kaplan-Meier survival curves will be used to determine outcome relative to genotype. | Baseline | No |
Primary | Whole-exome variant loci | Annotation and filtering of each whole-exome variant locus will be performed using a custom software pipeline. Variants in >= 2 OS cases will be validated, and then subsequently replicated in additional OS cases (samples previously received for the GWAS from international collaborators). Variants will also be evaluated for presence in known biologically plausible pathways and genes. | Baseline | No |
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