Prostate-specific membrane antigen PET-CT in patients with high-risk prostate cancer before curative-intent surgery or radiotherapy (proPSMA): a prospective, randomised, multicentre study. Issue 10231 (11th April 2020)

• Record Type: Journal Article
• Authors: Hofman, Michael S; Lawrentschuk, Nathan; Francis, Roslyn J; Tang, Colin; Vela, Ian; Thomas, Paul; Rutherford, Natalie; Martin, Jarad M; Frydenberg, Mark; Shakher, Ramdave; Wong, Lih-Ming; Taubman, Kim; Ting Lee, Sze; Hsiao, Edward; Roach, Paul; Nottage, Michelle; Kirkwood, Ian; Hayne, Dickon; Link, Emma; Marusic, Petra; Matera, Anetta; Herschtal, Alan; Iravani, Amir; Hicks, Rodney J; Williams, Scott; Murphy, Declan G
• Is Part Of: Lancet. Volume 395:Issue 10231(2020)
• Page Start: 1208
• Page End: 1216
• Publication Date: 2020-04-11
• Subjects: Medicine -- Periodicals; Medicine -- Periodicals; Medicine; Medicine; Electronic journals; Periodicals; 610.5
• DOI: 10.1016/S0140-6736(20)30314-7
• Languages: English
• ISSNs: 0140-6736

Abstract

Summary: Background: Conventional imaging using CT and bone scan has insufficient sensitivity when staging men with high-risk localised prostate cancer. We aimed to investigate whether novel imaging using prostate-specific membrane antigen (PSMA) PET-CT might improve accuracy and affect management. Methods: In this multicentre, two-arm, randomised study, we recruited men with biopsy-proven prostate cancer and high-risk features at ten hospitals in Australia. Patients were randomly assigned to conventional imaging with CT and bone scanning or gallium-68 PSMA-11 PET-CT. First-line imaging was done within 21 days following randomisation. Patients crossed over unless three or more distant metastases were identified. The primary outcome was accuracy of first-line imaging for identifying either pelvic nodal or distant-metastatic disease defined by the receiver-operating curve using a predefined reference-standard including histopathology, imaging, and biochemistry at 6-month follow-up. This trial is registered with the Australian New Zealand Clinical Trials Registry, ANZCTR12617000005358. Findings: From March 22, 2017 to Nov 02, 2018, 339 men were assessed for eligibility and 302 men were randomly assigned. 152 (50%) men were randomly assigned to conventional imaging and 150 (50%) to PSMA PET-CT. Of 295 (98%) men with follow-up, 87 (30%) had pelvic nodal or distant metastatic disease. PSMA PET-CT had a 27% (95% CI 23–31) greater accuracy than that of conventional imaging (92% [88–95] vs 65% [60–69]; p<0·0001). We found a lower sensitivity (38% [24–52] vs 85% [74–96]) and specificity (91% [85–97] vs 98% [95–100]) for conventional imaging compared with PSMA PET-CT. Subgroup analyses also showed the superiority of PSMA PET-CT (area under the curve of the receiver operating characteristic curve 91% vs 59% [32% absolute difference; 28–35] for patients with pelvic nodal metastases, and 95% vs 74% [22% absolute difference; 18–26] for patients with distant metastases). First-line conventional imaging conferred management change less frequently (23 [15%] men [10–22] vs 41 [28%] men [21–36]; p=0·008) and had more equivocal findings (23% [17–31] vs 7% [4–13]) than PSMA PET-CT did. Radiation exposure was 10·9 mSv (95% CI 9·8–12·0) higher for conventional imaging than for PSMA PET-CT (19·2 mSv vs 8·4 mSv; p<0·001). We found high reporter agreement for PSMA PET-CT (κ=0·87 for nodal and κ=0·88 for distant metastases). In patients who underwent second-line image, management change occurred in seven (5%) of 136 patients following conventional imaging, and in 39 (27%) of 146 following PSMA PET-CT. Interpretation: PSMA PET-CT is a suitable replacement for conventional imaging, providing superior accuracy, to the combined findings of CT and bone scanning. Funding: Movember and Prostate Cancer Foundation of Australia. Video Abstract: PSMA PET-CT in patients with high-risk prostate cancer Professor Michael Hofman introduces the paper on prostate-specific membrane antigen PET-CT in patients with high-risk prostate cancer YouTube link: https://youtu.be/QKxPgEdLO2E