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Correlation between histologic features and Decipher genomic risk in prostate cancer biopsies.

2/5 보강
Annals of diagnostic pathology 📖 저널 OA 3.2% 2022: 0/1 OA 2024: 0/3 OA 2025: 0/5 OA 2026: 1/19 OA 2022~2026 2026 Vol.83() p. 152642 Prostate Cancer Diagnosis and Treatm
Retraction 확인
출처
PubMed DOI OpenAlex 마지막 보강 2026-04-30

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
40 cases, 13 (32.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Unfavorable histology demonstrated high specificity (96.3%) and positive predictive value (87.5%), but limited sensitivity, identifying 7 of 13 high-risk cases (53.8%). These findings suggest that while adverse histologic features partially predict high genomic risk, genomic testing may identify additional high-risk tumors not captured by morphology alone, supporting its selective use.
OpenAlex 토픽 · Prostate Cancer Diagnosis and Treatment Prostate Cancer Treatment and Research Cancer Genomics and Diagnostics

Takeda K

📝 환자 설명용 한 줄

The Decipher genomic classifier refines risk stratification in prostate cancer, but its incremental value over biopsy pathology remains uncertain.

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • p-value p < 0.001
  • Specificity 96.3%

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↓ .bib ↓ .ris
APA Kotaro Takeda (2026). Correlation between histologic features and Decipher genomic risk in prostate cancer biopsies.. Annals of diagnostic pathology, 83, 152642. https://doi.org/10.1016/j.anndiagpath.2026.152642
MLA Kotaro Takeda. "Correlation between histologic features and Decipher genomic risk in prostate cancer biopsies.." Annals of diagnostic pathology, vol. 83, 2026, pp. 152642.
PMID 41962405 ↗

Abstract

The Decipher genomic classifier refines risk stratification in prostate cancer, but its incremental value over biopsy pathology remains uncertain. We evaluated the correlation between Decipher scores and clinicopathologic features in diagnostic prostate biopsies. We retrospectively reviewed 40 prostate biopsies with concurrent Decipher testing. Clinical variables (age, PSA, and clinical T stage) and pathologic features (ISUP Grade Group, percentage of Gleason pattern 4, cribriform morphology, tumor length, and perineural invasion) were analyzed. Decipher scores were assessed as continuous and categorical variables (low risk < 0.5; high risk ≥ 0.5). Biopsies were further classified as favorable or unfavorable histology, with unfavorable histology defined by high-risk features including large cribriform architecture (>0.25 mm). Of 40 cases, 13 (32.5%) were high genomic risk and 8 (20.0%) showed unfavorable histology. High-risk cases were significantly enriched for higher Grade Groups (92% vs. 26%), greater median Gleason pattern 4 (25% vs. 0%), and more frequent cribriform morphology (77% vs. 11%) (all p < 0.001). Decipher scores correlated moderately with Gleason pattern 4 percentage (R = 0.345). Unfavorable histology demonstrated high specificity (96.3%) and positive predictive value (87.5%), but limited sensitivity, identifying 7 of 13 high-risk cases (53.8%). These findings suggest that while adverse histologic features partially predict high genomic risk, genomic testing may identify additional high-risk tumors not captured by morphology alone, supporting its selective use.

🏷️ 키워드 / MeSH 📖 같은 키워드 OA만

같은 제1저자의 인용 많은 논문 (3)

🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반