Performance of LFSPRO TP53 germline carrier risk predictions compared to standard genetic counseling practice on prospectively collected probands.

Purpose: Current clinical guidelines for genetic testing for Li-Fraumeni Syndrome (LFS) have many limitations, primarily the criteria don't consider detailed personal and family history information and may miss many individuals with LFS. A personalized risk assessment tool, LFSPRO, was created to estimate a proband's risk for LFS based on personal and family history information. The purpose of this study is to compare LFSPRO to existing clinical criteria to determine if LFSPRO can outperform these tools. Additionally, we gauged genetic counselors' (GCs) experience using LFSPRO for their patients. Methods: Between December 2021 and March 2024, GCs identified patients concerning for LFS based on the patients' personal and family history information. This information was entered into LFSPRO to predict the risk to have a pathogenic/pathogenic (LP/P) germline TP53 variant. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) was compared between LFSPRO and Chompret criteria. Select GCs were asked to fill out surveys regarding their experience using LFSPRO following their genetic counseling appointments. Results: LFSPRO's sensitivity and specificity were 0.529 and 0.781 compared to Chompret's respective 0.235 and 0.677. Additionally, LFSPRO had a positive predictive value (PPV) of 0.30 compared to Chompret's 0.114. LFSPRO's risk prediction was concordant with genetic testing results in 75% of probands. Eighty-one percent of GC surveys reported LFSPRO being concordant with the GC's expectations and 75% would feel comfortable sharing the results with patients. Conclusion: LFSPRO showed improved sensitivity and specificity compared to Chompret criteria and GCs report a positive experience with LFSPRO. LFSPRO can be used to increase access to genetic testing for patients at risk for LFS and could help healthcare providers give more direct risk assessments regarding LFS testing and management for patients.

Validating Risk Prediction Models for Multiple Primaries and Competing Cancer Outcomes in Families With Li-Fraumeni Syndrome Using Clinically Ascertained Data.

PURPOSE: There exists a barrier between developing and disseminating risk prediction models in clinical settings. We hypothesize that this barrier may be lifted by demonstrating the utility of these models using incomplete data that are collected in real clinical sessions, as compared with the commonly used research cohorts that are meticulously collected. MATERIALS AND METHODS: Genetic counselors (GCs) collect family history when patients (ie, probands) come to MD Anderson Cancer Center for risk assessment of Li-Fraumeni syndrome, a genetic disorder characterized by deleterious germline mutations in the TP53 gene. Our clinical counseling-based (CCB) cohort consists of 3,297 individuals across 124 families (522 cases of single primary cancer and 125 cases of multiple primary cancers). We applied our software suite LFSPRO to make risk predictions and assessed performance in discrimination using AUC and in calibration using observed/expected (O/E) ratio. RESULTS: For prediction of deleterious TP53 mutations, we achieved an AUC of 0.78 (95% CI, 0.71 to 0.85) and an O/E ratio of 1.66 (95% CI, 1.53 to 1.80). Using the LFSPRO.MPC model to predict the onset of the second cancer, we obtained an AUC of 0.70 (95% CI, 0.58 to 0.82). Using the LFSPRO.CS model to predict the onset of different cancer types as the first primary, we achieved AUCs between 0.70 and 0.83 for sarcoma, breast cancer, or other cancers combined. CONCLUSION: We describe a study that fills in the critical gap in knowledge for the utility of risk prediction models. Using a CCB cohort, our previously validated models have demonstrated good performance and outperformed the standard clinical criteria. Our study suggests that better risk counseling may be achieved by GCs using these already-developed mathematical models.

Validating risk prediction models for multiple primaries and competing cancer outcomes in families with Li-Fraumeni syndrome using clinically ascertained data at a single institute.

Purpose: There exists a barrier between developing and disseminating risk prediction models in clinical settings. We hypothesize this barrier may be lifted by demonstrating the utility of these models using incomplete data that are collected in real clinical sessions, as compared to the commonly used research cohorts that are meticulously collected. Patients and methods: Genetic counselors (GCs) collect family history when patients (i.e., probands) come to MD Anderson Cancer Center for risk assessment of Li-Fraumeni syndrome, a genetic disorder characterized by deleterious germline mutations in the TP53 gene. Our clinical counseling-based (CCB) cohort consists of 3,297 individuals across 124 families (522 cases of single primary cancer and 125 cases of multiple primary cancers). We applied our software suite LFSPRO to make risk predictions and assessed performance in discrimination using area under the curve (AUC), and in calibration using observed/expected (O/E) ratio. Results: For prediction of deleterious TP53 mutations, we achieved an AUC of 0.81 (95% CI, 0.70 - 0.91) and an O/E ratio of 0.96 (95% CI, 0.70 - 1.21). Using the LFSPRO.MPC model to predict the onset of the second cancer, we obtained an AUC of 0.70 (95% CI, 0.58 - 0.82). Using the LFSPRO.CS model to predict the onset of different cancer types as the first primary, we achieved AUCs between 0.70 and 0.83 for sarcoma, breast cancer, or other cancers combined. Conclusion: We describe a study that fills in the critical gap in knowledge for the utility of risk prediction models. Using a CCB cohort, our previously validated models have demonstrated good performance and outperformed the standard clinical criteria. Our study suggests better risk counseling may be achieved by GCs using these already-developed mathematical models.

Cadaveric Study of Appropriate Screw Length for Distal Radius Stabilization Using Volar Plate Fixation.

We conducted a study to highlight areas of risk with distal radius fixation to prevent occurrence of extensor tendon injury without compromising the security and stability of the fixation. Twelve cadaveric forearms were used. The volar locking plate was placed to best anatomical and radiologic fit on the distal radius of each arm. All 7 holes in the plate were drilled, and bicortical length was measured using a depth gauge under fluoroscopy to estimate screw lengths. Screws were secured into place, and dorsal prominence was measured. The central screw positions had the least dorsal screw prominence, mean (SD) of 0.50 (1.06) mm, and were considered low-risk. The radial and ulnar screw positions had more dorsal screw prominence, 3.38 (1.38) mm and 1.03 (1.30) mm, respectively. Although only radial prominence was statistically significant, both radial and ulnar screw positions were considered high-risk and in need of screw length adjustments. The data suggest that screw length for this plate should be decreased by about 3 mm for the radial positions and by 1 mm for the ulnar positions to decrease the risk for tendon rupture and irritation secondary to dorsal screw prominence.