Volume 2, Issue 1 (Winter 2018)                   Multidiscip Cancer Investig 2018, 2(1): 22-25 | Back to browse issues page


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Abstract:   (1576 Views)
Introduction: Multiple myeloma is a heterogeneous disease with different survival times among patients. Accurate prediction of prognosis in multiple myeloma is essential, as patients with a shorter survival time may require early bone marrow transplantation (BMT) and more advanced chemotherapy as a part of their first-line treatment. In the present study, a parameter, depicted by gamma (γ) symbol, was utilized to categorize patients into different stages. Gamma value is equal to the summation of each prognostic factor multiplied by its corresponding beta coefficient. This parameter has been previously studied for the staging of some malignancies, such as “Nottingham Prognostic Index” for breast cancer and “Prognostic Score” for parotid carcinoma.
Methods: One hundred forty-three cases were randomly divided into two groups. Beta coefficients for prognostic factors, including creatinine, calcium, and albumin, were obtained from multivariate Cox analysis in the first group. In this group, a staging system based on patients’ gamma parameters was defined followed by the evaluation of the accuracy of this staging system in the second group.
Results: The staging system that developed from the first group was suitable for the prediction of outcomes in the second group. The patients of the second group were divided into approximately equal numbers in each stage comprising 29, 24, and 18 cases in stage 1, 2, and 3, respectively. In this group, the median overall survival (OS) values for patients in each stage were 92, 57, and 22 months, respectively, with log-rank = 0.002.
Conclusions: The proposed method demonstrated promising results for myeloma prognostication. The authors believe this approach would increase the strength and validity of staging of multiple myeloma.
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Type of Study: Short Communication | Subject: treatment
Received: 2017/12/12 | Accepted: 2018/01/10 | ePublished: 2018/01/15

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