Count Me In Metastatic Breast Cancer Cohort: Genetic Variants and Time to Metastasis

A secondary analysis of 63 female participants from the Count Me In Metastatic Breast Cancer Project. The dataset includes whole-exome sequencing data linked to medical records, focusing on single nucleotide polymorphisms in metastasis-related genes. The analysis identified CXCL12 and GAPDH as candidate genes associated with variation in metastatic progression timing.

Use Cases

• Training predictive models for time to metastasis based on genetic variants.
• Identifying candidate genes for targeted surveillance in metastatic breast cancer.
• Conducting sensitivity analyses of genetic associations using accelerated failure time models.

Strengths

• Includes 63 patient records with linked genomic and clinical data.
• Analysis identified two specific genetic variants (CXCL12 rs266091 and GAPDH rs1803622) meeting statistical significance thresholds.
• Time to metastasis is fully observed with detailed statistics (mean 732.6 days, median 132.0 days).

Limitations

• Row count for the underlying genomic data is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The sample size of 63 participants is relatively small for genetic association studies.

Provenance

Source

Count Me In: The Metastatic Breast Cancer Project (CMI-MBCProject), available through dbGaP (phs001709.v1.p1).

Collection Method

Secondary analysis of retrospectively ascertained time-to-event outcomes within a cross-sectional genomic dataset linked to medical and self-reported patient data.

Freshness

Last updated 2026-05-29 06:21:28; freshness should be verified.