Is Likert better than PI-RADS at predicting prostate cancer on MRI and can a mathematical algorithm achieve similar results?

BACKGROUND: Prostate Imaging Reporting & Data System (PI-RADS) is an internationally recognized system to quantify risk of prostate cancer on magnetic resonance imaging (MRI). However, studies have suggested methods to improve predictive accuracy. PURPOSE: To assess two different methods that aim to improve the accuracy of PI-RADS scores: a subjective Likert score given by experienced reporters, and an objective Calculated Adjustment of PI-RADS Equivocal Score (CAPES). MATERIAL AND METHODS: Five experienced reporters in a quaternary referral unit used a standardized reporting template to prospectively collect PI-RADS and Likert scores for 1467 multiparametric MRI (mpMRI) scans between January 2021 and June 2022. Histology results were recorded for patients who underwent trans-perineal biopsy. The CAPES tool was retrospectively applied to the cases scoring PI-RADS 3. A theoretical standardized biopsy protocol (assuming all patients scoring ≥3 were referred for biopsy) was used to compare the three scoring systems for sensitivity, specificity, and positive predictive value (PPV). RESULTS: Across all reporters, significantly fewer equivocal "3" scores were given using Likert (15.7%) or CAPES (2.2%) compared to PI-RADS (24.1%). Assuming a protocol where all patients scoring ≥3 were biopsied, Likert had a higher specificity (69.0% vs. 54.4%), sensitivity (98.3% vs. 97.7%), and PPV (49.9% vs. 40.3%) than PI-RADS for identifying ISUP ≥2 cancer. The CAPES tool had an even higher specificity (81.4%) and PPV (61.2%) with only a slightly lower sensitivity (93.4%) resulting in 37.1% (n = 316) fewer biopsies than PI-RADS, and 22.4% (n = 155) fewer biopsies than Likert across 1467 patients. CONCLUSIONS: Compared to PI-RADS scoring, Likert scoring or CAPES can result in fewer equivocal scores, greater PPV, and fewer unnecessary biopsies.

Does including histological outcomes in a multiparametric MRI report improve prostate biopsy decision making?

OBJECTIVES: To see if inserting audited histological outcome data for each Likert score into prostate mpMRI reports was helpful for clinicians counselling patients and influenced prostate biopsy uptake. METHODS: A single radiologist reported 791 mpMRI scans for query prostate cancer between 2017 and 2019. A structured template which included histological outcome data from this cohort was devised and included in 207 mpMRI reports between January and June 2021. The outcomes of the new cohort were compared with the historical cohort, and with 160 contemporaneous reports without histological outcome data from the four other radiologists in the department. The opinion of this template was sought from referring clinicians who counselled patients. RESULTS: The proportion of patients biopsied fell from 58.0 to 32.9% overall between the n = 791 cohort and the n = 207 cohort. This was most noticeable in those scoring Likert 3, where the proportion biopsied fell from 78.4 to 42.9%. This reduction was also seen when comparing the biopsy rates of patients scored Likert 3 by other reporters in a contemporaneous n = 160 cohort without the audit information (65.2%) with the n = 207 cohort (42.9%). 100% of counselling clinicians were in favour and 66.7% said it gave them greater confidence to advise the patient when they did not need a biopsy. CONCLUSION: Fewer low-risk patients choose unnecessary biopsies when audited histological outcomes for the radiologist's Likert scores are included in mpMRI reports. ADVANCES IN KNOWLEDGE: Clinicians welcome reporter-specific audit information in mpMRI reports which could result in fewer biopsies.

Making an art into a science: a mathematical "Likert tool" can change PI-RADS (v2) scores into Likert scores when reporting multiparametric MRI for prostate cancer.

BACKGROUND: When reporting multiparametric magnetic resonance imaging (mpMRI) for prostate cancer, UK national guidelines recommend allocating both Likert and PI-RAD scores. Likert scores have been shown to better predict clinically significant cancer (csPCa) but are subjective and lack standardization. PURPOSE: To compare differences in outcomes between the scoring systems and create a mathematical tool that can help to objectively allocate Likert scores. MATERIAL AND METHODS: A total of 791 patients referred with query prostate cancer between 2017 and 2019 were prospectively allocated PI-RADS and Likert scores by a single experienced reporter. Histology results were used to compare the predictive accuracy of both scoring systems. A "Likert tool" was created based on a logistic regression of features found to be predictors of csPCa in a cohort of 2018-2019 patients (n = 411). Its performance was evaluated. RESULTS: Assuming a policy whereby patients with a PI-RADS/Likert score of ≥3 are biopsied, Likert scoring (sensitivity 0.92, specificity 0.77) would have resulted in 107 fewer biopsies and 20.3% higher cancer yields than the PI-RADS score (sensitivity 0.99, specificity 0.43). Thirteen patients would have avoided over-diagnosis of clinically insignificant prostate cancer (iPCa). Similar outcomes (111 fewer biopsies, 22.3% increase in cancer yield, iPCa diagnosis avoided in 16 patients) could be seen when the "Likert tool" was applied to the same patient cohort (sensitivity 0.93, specificity 0.79) and to a separate cohort (n = 380). CONCLUSION: PI-RADS and Likert scores are different. A "Likert tool" could reduce inter-reporter variability, decrease the number of patients unnecessarily biopsied, increase csPCa yield, and decrease over-diagnosis of iPCa.

Patient non-attendance at urgent referral appointments for suspected cancer and its links to cancer diagnosis and one year mortality: A cohort study of patients referred on the Two Week Wait pathway.

BACKGROUND: The 'Two Week Wait' policy aims to ensure patients with suspected cancer are seen within two weeks of referral. However, patient non-attendance can result in this target being missed. This study aimed to identify predictors of non-attendance; and analyse the relationship between attendance and outcomes including cancer diagnosis and early mortality. METHODS: A cohort study of 109,433 adults registered at 105 general practices, referred to a cancer centre within a large NHS hospital trust (April 2009 to December 2016) on the 'Two Week Wait' pathway. RESULTS: 5673 (5.2%) patients did not attend. Non-attendance was largely predicted by patient factors (younger and older age, male gender, greater deprivation, suspected cancer site, earlier year of referral, greater distance to the hospital) over practice factors (greater deprivation, lower Quality and Outcomes Framework score, lower cancer conversion rate, lower cancer detection rate). 10,360 (9.6%) patients were diagnosed with cancer within six months of referral (9.8% attending patients, 5.6% non-attending patients). Among these patients, 2029 (19.6%) died within 12 months of diagnosis: early mortality risk was 31.3% in non-attenders and 19.2% in attending patients. CONCLUSIONS: Non-attendance at urgent referral appointments for suspected cancer involves a minority of patients but happens in predictable groups. Cancer diagnosis was less likely in non-attending patients but these patients had worse early mortality outcomes than attending patients. The study findings have implications for cancer services and policy.