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The Automated Bone Scan Index as a Predictor of Response to Prostate Radiotherapy in Men with Newly Diagnosed
Adnan Ali1, Alex P Hoyle2, Christopher C Parker3
1Genito-Urinary Cancer Research Group, Division of Cancer Sciences, The University of Manchester, Manchester, UK; FASTMAN Centre of Prostate Cancer Excellence, Manchester Cancer Research Centre, Manchester, UK; Department of Surgery, The Christie NHS Foundation Trust, Manchester, UK.
Background:
Prostate radiotherapy (RT) is a first-line option for newly diagnosed men with low-burden metastatic prostate cancer. The current criterion to define this clinical state is based on manual bone metastasis counts, but enumeration of bone metastases is limited by interobserver variations, and it does not account for metastasis volume or lesional coalescence. The automated bone scan index (aBSI) is a quantitative method of evaluating bone metastatic burden in a standardised and reproducible manner.
Objective:
To evaluate whether aBSI has utility as a predictive imaging biomarker to define a newly diagnosed metastatic prostate cancer population that might benefit from the addition of prostate RT to standard of care (SOC) systemic therapy.
Design, Setting, And Participants:
This is an exploratory analysis of men with newly diagnosed metastatic prostate cancer randomised in a 1:1 ratio to either SOC or SOC + prostate RT within the STAMPEDE "M1|RT comparison".
Intervention:
The SOC was lifelong androgen deprivation therapy, with up-front docetaxel permitted from December 2015. Men allocated RT received either a daily or a weekly schedule that was nominated before randomisation.
Outcome Measurements And Statistical Analysis:
Baseline bone scans were evaluated retrospectively to calculate aBSI. We used overall (OS) and failure-free (FFS) survival as the end points. Treatment-aBSI interaction was evaluated using the multivariable fractional polynomial interaction (MFPI) and subpopulation treatment effect pattern plot. Further analysis was done in aBSI quartiles using Cox regression models adjusted for stratification factors.
Results And Limitations:
Baseline bone scans for 660 (SOC: 323 and SOC + RT: 337) of 2061 men randomised within the "M1|RT comparison" met the software requirements for aBSI calculation. The median age was 68 yr, median PSA was 100 ng/mL, median aBSI was 0.9, and median follow-up was 39 mo. Baseline patient characteristics including aBSI were balanced between the treatment groups. Using the MFPI procedure, there was evidence of aBSI-treatment interaction for OS (p = 0.04, MFPI procedure) and FFS (p < 0.01, MFPI procedure). Graphical evaluation of estimated treatment effect plots showed that the OS and FFS benefit from prostate RT was greatest in patients with a low aBSI. Further analysis in quartiles based on aBSI supported this finding.
Conclusions:
A low automated bone scan index is predictive of survival benefit associated with prostate RT in men with newly diagnosed metastatic prostate cancer.
Patient Summary:
The widely used bone scan can be evaluated using an automated technique to potentially select men with newly diagnosed metastatic prostate cancer who might benefit from prostate radiotherapy.
