A high number of patients are suffering from prostate cancer (PCa) and a large fraction of these are the ones with non-metastatic disease. Importantly, it is very difficult to decide the course of treatment for these patients diagnosed with an earlier stage of the disease. There exists significant variation while deciding the treatment strategy for patients for example radical treatment for intermediate-risk patients. These decisions can have great psychological consequences for the patients.
In 2020, Thurtle et al developed a freely available online tool, Predict Prostate (prostate.predict.nhs.uk), a personalized risk communication tool for patients with non-metastatic PCa. Using clinical and individual characteristics input of patients, the tool can generate crucial information such as overall survival estimates, benefits of radical treatment, and potential side-effects of different treatment options. The tool shows higher efficiency than other contemporary available risk predictor models. However, none of the available risk predictors so far have been evaluated in a clinical trial setting for their clinical utility.
A multicenter randomized controlled trial enrolled 156 patients, of whom 81 patients were randomly assigned to standard of care (SOC) plus Predict Prostate arm, and 75 to SOC only. Overall characteristics were well balanced between both the arms, with the mean age of enrolled patients being 67 years and PSA of 6.9 ng/ml. The primary objectives of this study were to assess the tool’s impact on decision making and associated psychological aspects among newly diagnosed non-metastatic PCa patients. The secondary objective of the study was a prediction of survival estimates and their impact on patients by Predict Prostate vs the patient’s perception of survival and treatment benefits.
The Predict Prostate (mean=15.9) group had a 26% lower mean decisional conflict score (DCS) than those in the SOC arm (mean=21.5) (p=0.01). Additionally, an improvement on other subscales such as ‘effective decision’, ‘uncertainty’, and ‘value clarity’ indicates that the group using the Predict tool felt more informed and clearer about their decisions (all p <0.05). However, no significant difference was observed between both the groups in anxiety. The key finding of the study was the lowered patient perceived 15-year prostate cancer specific mortality (PCSM) and overall benefit from radical treatment in the Predict group (p<0.0001). More than half (58%) men reported that the Predict tool estimated lower PCSM than their expectations. Additionally, 1 in 3 men said that using the Predict tool would make them less likely to chose radical treatment whereas 38% reported no change in the decision based on the tools’ results. The patient’s feedback about the tool was highly positive where 90% patients found it useful, and 94% said that they would recommend to other patients with a similar condition.
CONCLUSION
A first randomized study has evaluated the clinical impact of an online tool Predict Prostate on non-metastatic PCa patients. The results of this study demonstrate that the Predict tool can support patients in complex decision making and realistic estimation of disease progression during the course of the disease.
Reference
Top
