ArticleOncology and therapy2025
Physician and Patient Preferences for the Treatment of Metastatic Castration-Sensitive and Castration-Resistant Prostate Cancer: A Best-Worst Scaling Study in Japan.
Article in Oncology and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Real-world Treatment Selection and Shared Decision-making in De Novo Metastatic Castration-sensitive Prostate Cancer in Japan.Cancer diagnosis & prognosisArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionDespite many prostate cancer (PC) treatment options in Japan, physicians' and patients' preferences in metastatic castration-sensitive PC (mCSPC) and castration-resistant PC (CRPC) are unclear.
methodsFor this cross-sectional study, an online questionnaire survey based on the best-worst scaling (profile case) approach was designed. Physicians' and patients' questionnaires, comprising six attributes (efficacy, safety, target patients, dosage, administration, and medical expenditures), had 24 and 26 items for mCSPC and CRPC surveys, respectively. Four items were presented during each session; respondents selected the "most important" and "least important" among these. The objective was to elicit attributes important for treatment and their relative importance levels among physicians and patients and to explore similarities and differences in choices. Multinomial logit and hierarchical Bayesian models were applied, and preferences were presented as relative importance and utility values.
resultsResponses of 177 physicians (urologists: 173; oncologists: 4) and 292 patients (mCSPC: 94; CRPC: 198) were analyzed. Most patients with CRPC (63.1%) had no metastases. Efficacy was the most important attribute overall. Physicians considered patient survival the most important among efficacy items (11.1%), whereas patients with mCSPC prioritized prevention of metastases spread (9.7%) and prostate-specific antigen (PSA) elevation (9.3%). In CRPC, both physicians and patients prioritized prevention of metastasis development or its spread (physicians: 9.6%; patients: 8.3%) and PSA elevation (physicians: 9.3%; patients: 7.9%). After efficacy, physicians prioritized items related to target patients (cardiovascular disorders; mCSPC: 4.8%; CRPC: 3.4%), whereas patients prioritized safety (mCSPC: falls or fractures [5.6%]; CRPC: liver dysfunction [4.7%]). Patients with mCSPC were also concerned about rising medical expenditures (5.4%).
conclusionTreatment efficacy was the most important attribute for both physicians and patients in Japan in mCSPC and CRPC settings, although their preferences differed in priority based on outcomes. These findings may be useful to improve shared decision-making for PC treatment in Japan.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.