LBPO.CL02 · 临床研究 · Late-Breaking
计算推理用于泛癌队列个体化治疗方案制定的临床疗效：一项由法国多学科肿瘤委员会讨论的真实世界经验分析
Clinical efficacy of computational reasoning for personalized treatment planning in a pan-cancer cohort discussed by a French multidisciplinary tumor board: A real-world experience-based analysis
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
数字化药物分配（Digital Drug Assignment，DDA）是一种计算推理模型，可针对个体完整的分子肿瘤图谱推荐抗癌治疗方案，并按其DDA评分进行排序。此前对SHIVA01队列的分析将较高的DDA评分与改善的结局相关联（Petak等，2021）。在此，我们在一个来自居里研究所（Institut Curie）分子肿瘤委员会（MTB）的广泛真实世界队列中评估了预先定义的DDA分层。
我们回顾性分析了394例MTB病例（2018—2022年，实体瘤成人患者），这些病例具有NGS/WES/WGS数据、治疗记录和结局资料。纳入了接受分子靶向药物（MTAs；n=134）或化疗（n=177）的患者。对所使用的MTAs（包括ICIs）赋予DDA评分，并分层为低（<0）、中等和高（≥1000）三个层级。在各层级之间以及与化疗相比，比较了PFS、OS、ORR、DCR和生存率。
临床结局随DDA层级升高而持续改善（见表）。中位PFS从3.4个月（低层级）增至6.8个月（高层级），中位OS从7.8个月增至16.6个月。中等层级的MTAs与化疗表现相似（mPFS 4.5 vs 4.9个月；mOS 9.0 vs 9.8个月）。ORR、DCR、6个月PFS和24个月OS在各层级间均呈现积极趋势。DDA高层级治疗带来的获益最大，而DDA低层级的MTAs表现逊于化疗。无分子—药物关联的病例（n=5）结局最差（mPFS和mOS分别为2.6和6.5个月）。
在这一大型真实世界泛癌队列中，DDA利用每例患者的完整分子图谱，稳健地按临床疗效区分了不同治疗方案，独立验证了预先设定的DDA各层级间治疗—结局关联的一致性。这些结果促使将DDA的计算推理整合到MTB工作流程中，以确保精准肿瘤学实施中一致、高水平的临床表现与安全性。
DDA低层级（n = 13）DDA中等层级（n = 78）DDA高层级（n = 43）统计检验 化疗（n = 177） mPFS（月）3.4 4.5 6.8 HR 高 vs 低 = 0.35；log-rank p = 0.0006 4.9 mOS（月）7.8 9.0 16.6 HR 高 vs 低 = 0.45；log-rank p = 0.0190 9.8 ORR（%）8 19 33 趋势χ² 检验 p = 0.0283 16 DCR（%）31 45 64 趋势χ² 检验 p = 0.0148 42 6个月PFS率（%）15 29 47 趋势χ² 检验 p = 0.0168 33 24个月OS率（%）0 5 16 趋势χ² 检验 p = 0.0185 10
查看英文原文 English abstract
Digital Drug Assignment (DDA) is a computational reasoning model that recommends cancer therapies for the complete individual molecular tumor profiles and ranks them by their DDA scores. Prior analysis of the SHIVA01 cohort linked higher DDA scores to improved outcomes (Petak et al., 2021). Here, we evaluated predefined DDA tiers in a broad, real-world cohort from Institut Curie's Molecular Tumor Board (MTB).
We retrospectively analyzed 394 MTB cases (2018-2022, adults w solid tumors) with NGS/WES/WGS data, treatment records, and outcomes. Patients receiving molecularly targeted agents (MTAs; n=134) or chemotherapy (n=177) were included. Administered MTAs (including ICIs) were assigned DDA scores and stratified into low (<0), intermediate, and high (≥1000) tiers. PFS, OS, ORR, DCR, and survival rates were compared across tiers and in relation to chemotherapy.
Clinical outcomes improved consistently with higher DDA tiers (see table). Median PFS increased from 3.4 (low) to 6.8 months (high), and median OS from 7.8 to 16.6 months. Intermediate-tier MTAs performed similarly to chemotherapy (mPFS 4.5 vs 4.9 months; mOS 9.0 vs 9.8 months). ORR, DCR, 6-month PFS and 24-month OS all showed positive trends across tiers. DDA-high therapies provided the largest benefit, while DDA-low MTAs underperformed chemotherapy. Cases with no molecular-drug link (n=5) had the poorest outcomes (mPFS and mOS: 2.6 and 6.5 months).
In this large, real-world pan-cancer cohort, DDA robustly differentiated therapies by clinical efficacy using each patient's full molecular profile, independently validating the consistency of treatment-outcome associations across pre-established DDA tiers. These results urge the integration of DDA's computational reasoning into MTB workflows to ensure consistent, high clinical performance and safety in the implementation of precision oncology.
DDA-low (n = 13) DDA-intermediate (n = 78) DDA-high (n = 43) Statistical test Chemo (n = 177) mPFS (months) 3.4 4.5 6.8 HR high vs low = 0.35; log-rank p = 0.0006 4.9 mOS (months) 7.8 9.0 16.6 HR high vs low = 0.45; log-rank p = 0.0190 9.8 ORR (%) 8 19 33 Χ² for trend p = 0.0283 16 DCR (%) 31 45 64 Χ² for trend p = 0.0148 42 6-month PFS rate (%) 15 29 47 Χ² for trend p = 0.0168 33 24-month OS rate (%) 0 5 16 Χ² for trend p = 0.0185 10
利益披露 Disclosure
B. Vodicska,
Genomate Health Employment.
E. Kispeter,
Genomate Health Employment.
D. Lakatos,
Genomate Health Employment.
G. G. Kalmar,
Genomate Health Employment.
R. Doczi,
Genomate Health Employment.
D. Gorog-Tihanyi,
Genomate Health Employment.
A. Dirner,
Genomate Health Employment.
W. T. Beck,
Genomate Health Stock, Stock Option.
I. Bieche, None.
E. Borcoman,
Eisai, MSD, Sandoz, and Amgen Honoraria.
Daiichi Sankyo, Eisai, Amgen, Sandoz, MSD, Bristol-Myers Squibb, Novartis, Pfizer, and Roche meetings/travel grants and nonfinancial support.
N. Servant, None..
K. Nedara, None..
S. Watson, None..
C. Dupain, None.
I. Petak,
Genomate Health Employment.
C. Le Tourneau,
Transgene, MSD, LEO Pharma, BMS, J&J, DOB Pharmaceuticals, Bicara, Merus, Immutep, Owkin, Roche, GSK, Clinigen, Merck Serono, Aveon, ALX Oncology, Seagen Other, Advisory Board.