DOI: 10.1111/ggi.70720 ISSN: 1444-1586

Full‐Component Chart‐Derived Lee Score, Upfront Androgen Receptor Signaling Inhibitor Selection, and Competing Mortality in Metastatic Hormone‐Sensitive Prostate Cancer

Koichiro Kurokawa, Satoshi Yamamoto, Keita Higa, Hiroki Bamba, Sanji Kanaoka, Kazuyoshi Nakamura

ABSTRACT

Aim

To examine associations of a full‐component chart‐derived Lee score with upfront androgen receptor signaling inhibitor (ARSI) selection and competing mortality in men with metastatic hormone‐sensitive prostate cancer (mHSPC).

Methods

Of 136 potentially eligible patients receiving docetaxel‐free first‐line therapy, 96 with direct pretreatment documentation of all four functional items were included. The 12‐component score used the original point allocations and was analyzed continuously. Upfront ARSI receipt was evaluated using adjusted Firth logistic regression. Other‐cause mortality was assessed using univariable cause‐specific Cox and Fine–Gray models.

Results

Thirty‐three patients (34.4%) received upfront ARSI. Median age was 80 years and median score was 11. In the adjusted model ( n  = 91), a higher score showed an uncertain inverse association with upfront ARSI receipt (odds ratio per point, 0.84; 95% confidence interval [CI], 0.69–1.01; p  = 0.066). The reverse Kaplan–Meier estimate of median follow‐up was 37 months. Twenty‐nine deaths occurred, including 17 from other causes. In univariable Cox analysis, a higher score was associated with other‐cause death (hazard ratio per point, 1.16; 95% CI, 1.02–1.32; p  = 0.028), with a similar Fine–Gray estimate. Forty patients were excluded for incomplete functional documentation; included and excluded patients differed in age, albumin, ARSI use, and observed follow‐up.

Conclusions

The score showed a possible inverse relation with treatment intensification and was associated with other‐cause mortality. Because the analysis used an item‐complete subset with few competing events, the findings are exploratory. Direct functional assessment should inform treatment individualization.

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