Bone scan software predicts survival for metastatic prostate cancer
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Software that automatically analyzes bone scans accurately calculated the prognosis of men with bone metastatic castration-resistant prostate cancer, study data showed.
“This study describes major improvements over older techniques doctors used to measure bone metastases to predict survival and help guide treatments for patients with advanced prostate cancer,” Andrew Armstrong, MD, associate professor of medicine and surgery and assistant director of Duke Cancer Institute Prostate and Urologic Cancer Center, said in a press release. “It’s important to know how widespread metastatic disease is — both for patients to understand the likely course of their disease, and for doctors to determine the best potential treatments. It [also is] a necessary point of reference in clinical trials, to understand whether investigational therapies are working and to quantify and predict possible outcomes.”
The researchers performed a planned secondary analysis of 721 men (mean age, 70.6 years) from a phase 3 multicenter randomized, double-blind, placebo-controlled trial of the automated Bone Scan Index — an automated assessment of bone scan data that represents the total tumor burden as the fraction of total skeleton weight — that included 1,245 men with bone metastatic, chemotherapy-naive, castration-resistant prostate cancer from 37 countries. Patients included in the secondary analysis had baseline characteristics considered representative of the total study population.
Median automated Bone Scan Index in the cohort was 1.07 (range, 0-32.6). Researchers divided patients into four quartiles based on their index: 180 in quartile 1 (median, 0.05; range, 0-0.27), 181 in quartile 2 (median, 0.58; range, 0.28-1.07), 180 in quartile 3 (median, 2.06; range, 1.08-3.96) and 180 in quartile 4 (median, 6.72; range, 2.97-32.6).
Men in the lowest quartile achieved a median OS of 34.7 months, followed by 27.3 months in quartile 2, 21.7 months in quartile 3 and 13.3 months in quartile 4.
Researchers observed a significant association between the automated Bone Scan Index and OS (HR = 1.2; 95% CI, 1.14-1.26), indicating risk for death increased 20% per doubling of the index.
Compared with patients in quartile 4, researchers calculated reductions in risk for death of 65% for quartile 1, 56% for quartile 2 and 40% for quartile 3.
The automated Bone Scan Index had a significantly higher discriminative ability for prognosticating OS than manual lesion counting (C index, 0.63 vs. 0.6; P = .03).
The association between OS and a higher index score persisted in a multivariable survival model (HR = 1.06; 95% CI, 1.01-1.11).
Higher index score also appeared independently linked with time to progression of symptoms (HR = 1.18; 95% CI, 1.13-1.23), as well as time to use of opiates for cancer pain (HR = 1.21; 95% CI, 1.14-1.3) and prostate cancer-specific survival (HR = 1.2; 95% CI, 1.14-1.3).
If validated, this tool may have great use in evaluating response and resistant to therapy, Fred Saad, MD, FRCS, full professor and chief of urologic oncology at University of Montreal Hospital Center, wrote in an accompanying editorial.
“This is extremely important for anyone who realizes the time and effort required for comparing bone scans to determine whether or not patients are progressing on clinical trials,” he wrote.
“With the advent of more expensive and less widely available imaging modalities, such as prostate-specific membrane antigen PET or whole-body MRI, the automated Bone Scan Index becomes an attractive alternative if the results continue to be convincing,” he added. “Determining where the automated Bone Scan Index will fit in the rapidly growing field of imaging and how it compares and adds to imaging in terms of feasibility, cost and acceptability in the clinic will be a priority.” – by Andy Polhamus
Disclosures: Armstrong reports research funding from Active Biotech. Please see the study for a list of all other authors’ relevant financial disclosures. Saad reports no relevant financial disclosures.