Abbadi Ahmad, Eklund Martin, Lantz Anna, Discacciati Andrea, Björnebo Lars, Palsdottir Thorgerdur, Chandra Engel Jan, Jäderling Fredrik, Falagario Ugo, Grönberg Henrik, Nordström Tobias
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.
Department of Molecular Medicine and Surgery (Solna), Karolinska Institutet, Stockholm, Sweden.
EClinicalMedicine. 2025 Apr 3;82:103191. doi: 10.1016/j.eclinm.2025.103191. eCollection 2025 Apr.
Indeterminate lesions on prostate MRI, such as PI-RADS 3, present a clinical challenge due to their equivocal nature, complicating biopsy decisions in men undergoing testing for prostate cancer. Understanding the predictive capacity of biomarkers and risk calculators is critical to improve clinical decision-making and reduce unnecessary biopsies.
In this prospective cohort study, men with PI-RADS 3 findings on biparametric MRI (bp-MRI) who underwent combined biopsy (fusion targeted and systematic) in the STHLM3-MRI randomised clinical trial (first- and second-rounds) and at Capio St Göran's Hospital (Capio PCC), Sweden were included, representing screening-by-invitation, repeat screening, and clinical practice cohorts, respectively. Data collection occurred between Feb 5th, 2018, and Mar 4th, 2020, for STHLM3-MRI first-round screening, between Nov 10th, 2021, and Feb 20th, 2023 for second-round screening, and between Jan 7th, 2017 and June 30th, 2023 for Capio PCC. The data was collected directly from the participating laboratories using standardized reporting forms, medical charts, and additional study-specific data collection forms filled by patients. The primary outcome was detection of clinically significant prostate cancer (csPCa; ISUP ≥2) in men with PSA ≥3 ng/mL confirmed by the combined biopsy. The predictive capacity of the evaluated biomarkers (PSA density, the Stockholm3 test, prostate volume, MRI lesion volume ratio, and Stockholm3 density), as well as seven risk calculators, was assessed via the area under the curve (AUC) computed using logistic regression. Sensitivity and specificity of detecting csPCa and high-grade prostate cancer (ISUP ≥3) were reported. Complete-case analysis was performed for men with complete data on their PSA, prostate volume, Stockholm3 test, MRI lesion volume, findings on the digital rectal examination, family history of prostate cancer, and previous biopsy. The findings were contrasted to the analysis from the imputed dataset.
Of the 6554 men included into the three cohorts, 1187 received PI-RADS score of 3 on the bp-MRI, and 1146 underwent combined biopsy. Of them, 900 had PSA ≥3 ng/mL, and 656 men were included in the complete-case analysis (169 from STHLM3-MRI first-round, 72 from the second-round, and 415 from Capio PCC). Overall, 370/900 men (41%) and 258/656 men (39%) had ISUP ≥2, but only 75/900 (8%) and 50/656 (8%) had ISUP ≥3. PSA density, tested risk calculators, and probability tests had low-to-moderate AUC (range 0.50-0.73; PSA density range 0.58-0.66, Stockholm3 range 0.59-0.67, lesion volume ratio range 0.54-0.63), and performed similarly across individual cohorts and the combined dataset in the complete-case and imputed dataset analysis. For detection of ISUP ≥2 based on STHLM3-MRI first-round, PSA density at 0.10 had a sensitivity of 69% (56%, 80%), specificity of 49% (39%, 58%), and missing 27% (6%, 61%) of ISUP ≥3, while a PSA density of 0.15 had a sensitivity of 37% (25%, 50%), specificity of 84% (76%, 90%), missing 45% (17%, 70%) of ISUP ≥3. The best-performing model based on STHLM3-MRI included age, prostate volume, Stockholm3 density and MRI lesion ratio, and reduced prostate biopsies by 33% (26%, 40%) while maintaining 98% (91%, 100%) sensitivity to detect ISUP ≥2 cancer, specificity of 50% (41%, 60%) and AUC of 0.82 (0.76, 0.87). Meanwhile, the best-performing model based on the complete-case combined dataset included age, prostate volume, PSA density, and Stockholm3 density, and reduce prostate biopsies by 26% (23%, 30%) with a sensitivity of 90% (85%, 93%), specificity of 36% (31%, 41%), and AUC of 0.70 (0.66, 0.74).
Current risk-stratification tools and individual biomarkers perform suboptimally for guiding biopsy decisions in men with PI-RADS 3 lesions. The findings highlight the limitations of relying on PSA density alone and emphasize the need for caution in clinical recommendations. However, multiplex models might offer possibility to reduce unnecessary biopsies while maintaining high sensitivity for clinically significant prostate cancer detection. These findings should be externally validated and evaluated for cost-effectiveness.
STHLM3-MRI clinical trial is funded by the Swedish Cancer Society (Cancerfonden), the Swedish Research Council (Vetenskapsrådet), the Swedish Research Council for Health Working Life and Welfare (FORTE), the Strategic Research Programme on Cancer (StratCan), Hagstrandska Minnesfonden, Region Stockholm, Svenska Druidorden, Åke Wibergs Stiftelse, the Swedish e-Science Research Centre, the Karolinska Institutet, and Prostatacancerförbundet.
前列腺MRI上的不确定病变,如前列腺影像报告和数据系统(PI-RADS)3类病变,因其性质不明确而带来临床挑战,使接受前列腺癌检测的男性的活检决策变得复杂。了解生物标志物和风险计算器的预测能力对于改善临床决策和减少不必要的活检至关重要。
在这项前瞻性队列研究中,纳入了在斯德哥尔摩3-MRI随机临床试验(第一轮和第二轮)以及瑞典卡皮奥圣戈兰医院(卡皮奥前列腺癌中心)接受联合活检(融合靶向活检和系统活检)且在双参数MRI(bp-MRI)上有PI-RADS 3类结果的男性,分别代表受邀筛查、重复筛查和临床实践队列。数据收集时间为:斯德哥尔摩3-MRI第一轮筛查在2018年2月5日至2020年3月4日之间,第二轮筛查在2021年11月10日至2023年2月20日之间,卡皮奥前列腺癌中心在2017年1月7日至2023年6月30日之间。数据通过标准化报告表、病历以及患者填写的额外特定研究数据收集表直接从参与实验室收集。主要结局是在联合活检确诊PSA≥3 ng/mL的男性中检测出临床显著前列腺癌(csPCa;国际泌尿病理学会[ISUP]≥2级)。通过逻辑回归计算的曲线下面积(AUC)评估所评估的生物标志物(PSA密度、斯德哥尔摩3检测、前列腺体积、MRI病变体积比和斯德哥尔摩3密度)以及七种风险计算器的预测能力。报告了检测csPCa和高级别前列腺癌(ISUP≥3级)的敏感性和特异性。对PSA、前列腺体积、斯德哥尔摩3检测、MRI病变体积、直肠指检结果、前列腺癌家族史和既往活检有完整数据的男性进行了完整病例分析。将研究结果与插补数据集的分析结果进行对比。
在纳入三个队列的6554名男性中,1187名在bp-MRI上获得PI-RADS 3分,1146名接受了联合活检。其中,900名PSA≥3 ng/mL,656名男性纳入完整病例分析(斯德哥尔摩3-MRI第一轮169名,第二轮72名,卡皮奥前列腺癌中心415名)。总体而言,900名男性中有370名(41%)、656名男性中有258名(39%)ISUP≥2级,但只有900名中的75名(8%)和656名中的50名(8%)ISUP≥3级。PSA密度、经过测试的风险计算器和概率测试的AUC较低至中等(范围0.50 - 0.73;PSA密度范围0.58 - 0.66,斯德哥尔摩3范围0.59 - 0.67,病变体积比范围0.54 - 0.63),在完整病例和插补数据集分析中,各个队列和合并数据集的表现相似。基于斯德哥尔摩3-MRI第一轮检测ISUP≥2级时,PSA密度为0.10时敏感性为69%(56%,80%),特异性为49%(39%,58%),漏诊27%(6%,61%)的ISUP≥3级,而PSA密度为0.15时敏感性为37%(25%,50%),特异性为84%(76%,90%),漏诊45%(17%,70%)的ISUP≥3级。基于斯德哥尔摩3-MRI的最佳模型包括年龄、前列腺体积、斯德哥尔摩3密度和MRI病变比例,可减少33%(26%,40%)的前列腺活检,同时保持98%(91%,100%)的敏感性以检测ISUP≥2级癌症,特异性为50%(41%,60%),AUC为0.82(0.76,0.87)。同时,基于完整病例合并数据集的最佳模型包括年龄、前列腺体积、PSA密度和斯德哥尔摩3密度,可减少26%(23%,30%)的前列腺活检,敏感性为90%(85%,93%),特异性为36%(31%,41%),AUC为0.70(0.66,0.74)。
当前的风险分层工具和单个生物标志物在指导有PI-RADS 3类病变男性的活检决策方面表现欠佳。研究结果突出了仅依赖PSA密度的局限性,并强调临床建议时需谨慎。然而,多因素模型可能提供减少不必要活检的可能性,同时保持对临床显著前列腺癌检测的高敏感性。这些研究结果应进行外部验证并评估其成本效益。
斯德哥尔摩3-MRI临床试验由瑞典癌症协会(Cancerfonden)、瑞典研究理事会(Vetenskapsrådet)、瑞典健康、工作生活与福利研究理事会(FORTE)、癌症战略研究计划(StratCan)、哈格斯特兰纪念基金会、斯德哥尔摩地区、瑞典共济会、奥克·维伯格基金会、瑞典电子科学研究中心、卡罗琳斯卡学院和前列腺癌协会资助。