Dataset Information

A mathematical model for short-term vs. long-term survival in patients with glioma.

ABSTRACT: Gliomas, the most common primary brain tumors in adults, constitute clinically, histologically, and molecularly a most heterogeneous type of cancer. Owing to this, accurate clinical prognosis for short-term vs. long-term survival for patients with grade II or III glioma is currently nonexistent. A rigorous, multi-method bioinformatic approach was used to identify the top most differentially expressed genes as captured by mRNA sequencing of tumor tissue. Mathematical modeling was employed to develop the model, and three different and independent methods of validation were used to assess its performance. I present here a mathematical model that can identify with a high accuracy (sensitivity=92.9%, specificity=96.0%) those patients with glioma (grade II or III) who will experience short-term survival (? 1 year), as well as those with long-term survival (? 3 years), at the time of diagnosis and prior to surgery and adjuvant chemotherapy. The 5 gene input variables to the model are: FAM120AOS, PDLIM4, OCIAD2, PCDH15, and MXI1. MXI1, a transcriptional repressor, represents the top biomarker of survival and the most promising target for the development of a pharmacological treatment.

SUBMITTER: Nikas JB

PROVIDER: S-EPMC4266718 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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A mathematical model for short-term vs. long-term survival in patients with glioma.

Nikas Jason B JB

American journal of cancer research 20141119 6

Gliomas, the most common primary brain tumors in adults, constitute clinically, histologically, and molecularly a most heterogeneous type of cancer. Owing to this, accurate clinical prognosis for short-term vs. long-term survival for patients with grade II or III glioma is currently nonexistent. A rigorous, multi-method bioinformatic approach was used to identify the top most differentially expressed genes as captured by mRNA sequencing of tumor tissue. Mathematical modeling was employed to deve ...[more]

PMID: 25520874

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Project description:Although partial nephrectomy is the preferred treatment for many patients with early-stage kidney cancer, recent clinical trial data, which demonstrate better survival for patients treated with radical nephrectomy, have generated new uncertainty regarding the comparative effectiveness of these treatment options.To compare long-term survival after partial vs radical nephrectomy among a population-based patient cohort whose treatment reflects contemporary surgical practice.We performed a retrospective cohort study of Medicare beneficiaries with clinical stage T1a kidney cancer treated with partial or radical nephrectomy from 1992 through 2007. Using an instrumental variable approach to account for measured and unmeasured differences between treatment groups, we fit a 2-stage residual inclusion model to estimate the treatment effect of partial nephrectomy on long-term survival.Overall and kidney cancer-specific survival.Among 7138 Medicare beneficiaries with early-stage kidney cancer, we identified 1925 patients (27.0%) treated with partial nephrectomy and 5213 patients (73.0%) treated with radical nephrectomy. During a median follow-up of 62 months, 487 (25.3%) and 2164 (41.5%) patients died following partial or radical nephrectomy, respectively. Kidney cancer was the cause of death for 37 patients (1.9%) treated with partial nephrectomy, and 222 patients (4.3%) treated with radical nephrectomy. Patients treated with partial nephrectomy had a significantly lower risk of death (hazard ratio [HR], 0.54; 95% CI, 0.34-0.85). This corresponded with a predicted survival increase with partial nephrectomy of 5.6 (95% CI, 1.9-9.3), 11.8 (95% CI, 3.9-19.7), and 15.5 (95% CI, 5.0-26.0) percentage points at 2, 5, and 8 years posttreatment (P < .001). No difference was noted in kidney cancer-specific survival (HR, 0.82; 95% CI, 0.19-3.49).Among Medicare beneficiaries with early-stage kidney cancer who were candidates for either surgery, treatment with partial rather than radical nephrectomy was associated with improved survival.

Dataset Information

A mathematical model for short-term vs. long-term survival in patients with glioma.

Publications

A mathematical model for short-term vs. long-term survival in patients with glioma.

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