Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer.

PURPOSE: Determining the frequency and distribution of pathogenic germline variants (PGVs) in Austrian prostate cancer (PCa) patients and to assess the accuracy of different clinical risk scores to correctly predict PGVs. METHODS: This cross-sectional study included 313 men with advanced PCa. A comprehensive personal and family history was obtained based on predefined questionnaires. Germline DNA sequencing was performed between 2019 and 2021 irrespective of family history, metastatic or castration status or age at diagnosis. Clinical risk scores for hereditary cancer syndromes were evaluated and a PCa-specific score was developed to assess the presence of PGVs. RESULTS: PGV presence was associated with metastasis (p = 0.047) and castration resistance (p = 0.011), but not with personal cancer history or with relatives with any type of cancer. Clinical risk scores (Manchester score, PREMM5 score, Amsterdam II criteria or Johns Hopkins criteria) showed low sensitivities (3.3-20%) for assessing the probability of PGV presence. A score specifically designed for PCa patients stratifying patients into low- or high-risk regarding PGV probability, correctly classified all PGV carriers as high-risk, whereas a third of PCa patients without PGVs was classified as low risk of the presence of PGVs. CONCLUSION: Application of common clinical risk scores based on family history are not suitable to identify PCa patients with high PGV probabilities. A PCa-specific score stratified PCa patients into low- or high-risk of PGV presence with sufficient accuracy, and germline DNA sequencing may be omitted in patients with a low score. Further studies are needed to evaluate the score.

Breast MRI: does a clinical decision algorithm outweigh reader experience?

OBJECTIVES: Due to its high sensitivity, DCE MRI of the breast (MRIb) is increasingly used for both screening and assessment purposes. The Kaiser score (KS) is a clinical decision algorithm, which formalizes and guides diagnosis in breast MRI and is expected to compensate for lesser reader experience. The aim was to evaluate the diagnostic performance of untrained residents using the KS compared to off-site radiologists experienced in breast imaging using only MR BI-RADS. METHODS: Three off-site, board-certified radiologists, experienced in breast imaging, interpreted MRIb according to the MR BI-RADS scale. The same studies were read by three residents in radiology without prior training in breast imaging using the KS. All readers were blinded to clinical information. Histology was used as the gold standard. Statistical analysis was conducted by comparing the AUC of the ROC curves. RESULTS: A total of 80 women (median age 52 years) with 93 lesions (32 benign, 61 malignant) were included. The individual within-group performance of the three expert readers (AUC 0.723-0.742) as well as the three residents was equal (AUC 0.842-0.928), p > 0.05, respectively. But, the rating of each resident using the KS significantly outperformed the experts' ratings using the MR BI-RADS scale (p ≤ 0.05). CONCLUSION: The KS helped residents to achieve better results in reaching correct diagnoses than experienced radiologists empirically assigning MR BI-RADS categories in a clinical "problem solving MRI" setting. These results support that reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience. KEY POINTS: • Reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience in a clinical "problem solving MRI" setting. • The Kaiser score, which provides a clinical decision algorithm for structured reporting, helps residents to reach an expert level in breast MRI reporting and to even outperform experienced radiologists using MR BI-RADS without further formal guidance.

Mechanisms of heart failure in transthyretin vs. light chain amyloidosis.

AIMS: Cardiac amyloidosis (CA) leads to signs and symptoms of heart failure (HF). The mechanisms of biventricular dysfunction and their impact on outcome in subtypes of CA are poorly understood. Our aim was to compare right ventricular (RV) and left ventricular (LV) parameters in patients with light chain (AL) and wild-type transthyretin amyloidosis (ATTRw) and evaluate their ability to predict cardiac outcome. METHODS AND RESULTS: We included patients with CA into a prospective registry. Baseline assessment included biventricular 2D speckle tracking imaging parameters. Patients were followed-up in regular intervals. The composite endpoint was defined as cardiovascular death, heart transplantation or ventricular assist device implantation, and HF hospitalization. We included 122 patients with CA. Sixty-two of these patients (50.8%) were diagnosed with ATTRw and 60 (49.2%) with AL. In ATTRw, parameters of RV size and function correlated well with symptom severity and only morphological and functional parameters of the RV predicted outcome. RV free wall strain was the only independent predictor of outcome with a hazard ratio (HR) of 1.185 [95% confidence interval (CI) 1.047-1.342, P = 0.007]. In AL on the other hand, RV function correlated well with symptoms but was not associated with outcome. In contrast, global longitudinal strain of the LV (LV-GLS) was predictive for outcome. After adjusting in a multivariable model, LV-GLS remained predictive with a HR of 1.180 (95% CI 1.032-1.348, P = 0.015). CONCLUSION: Our data suggest that mechanisms underlying HF differ between ATTRw and AL. This may have substantial implications in particular in light of emerging therapies for both subtypes of CA.