2 research outputs found
External Validation of Models Predicting the Probability of Lymph Node Involvement in Prostate Cancer Patients
Background: Multiple statistical models predicting lymph node involvement (LNI) in prostate cancer (PCa) exist to support clinical decision-making regarding extended pelvic lymph node dissection (ePLND). Objective: To validate models predicting LNI in Dutch PCa patients. Design, setting, and participants: Sixteen prediction models were validated using a patient cohort of 1001 men who underwent ePLND. Patient characteristics included serum prostate specific antigen (PSA), cT stage, primary and secondary Gleason scores, number of biopsy cores taken, and number of positive biopsy cores. Outcome measurements and statistical analysis: Model performance was assessed using the area under the receiver operating characteristic curve (AUC). Calibration plots were used to visualize over- or underestimation by the models. Results and limitations: LNI was identified in 276 patients (28%). Patients with LNI had higher PSA, higher primary Gleason pattern, higher Gleason score, higher number of nodes harvested, higher number of positive biopsy cores, and higher cT stage compared to patients without LNI. Predictions generated by the 2012 Briganti nomogram (AUC 0.76) and the Memorial Sloan Kettering Cancer Center (MSKCC) web calculator (AUC 0.75) were the most accurate. Calibration had a decisive role in selecting the most accurate models because of overlapping confidence intervals for the AUCs. Underestimation of LNI probability in patients had a predicted probability of <20%. The omission of model updating was a limitation of the study. Conclusions: Models predicting LNI in PCa patients were externally validated in a Dutch patient cohort. The 2012 Briganti and MSKCC nomograms were identified as the most accurate prediction models available. Patient summary: In this report we looked at how well models were able to predict the risk of prostate cancer spreading to the pelvic lymph nodes. We found that two models performed similarly in predicting the most accurate probabilities. Nomograms developed by Briganti et al and the Memorial Sloan Kettering Cancer Center were best at predicting lymph node involvement in prostate cancer patients. These models support clinical decision-making on whether to perform pelvic lymph node dissection
Optimizing the risk threshold of lymph node involvement for performing extended pelvic lymph node dissection in prostate cancer patients: a cost-effectiveness analysis
Background: Extended pelvic lymph node dissection (ePLND) may be omitted in prostate cancer (CaP) patients with a low predicted risk of lymph node involvement (LNI). The aim of the current study was to quantify the cost-effectiveness of using different risk thresholds for predicted LNI in CaP patients to inform decision making on omitting ePLND. Methods: Five different thresholds (2%, 5%, 10%, 20%, and 100%) used in practice for performing ePLND were compared using a decision analytic cohort model with the 100% threshold (i.e., no ePLND) as reference. Compared outcomes consisted of quality-adjusted life years (QALYs) and costs. Baseline characteristics for the hypothetical cohort were based on an actual Dutch patient cohort containing 925 patients who underwent ePLND with risks of LNI predicted by the Memorial Sloan Kettering Cancer Center web-calculator. The best strategy was selected based on the incremental cost effectiveness ratio when applying a willingness to pay (WTP) threshold of €20,000 per QALY gained. Probabilistic sensitivity analysis was performed with Monte Carlo simulation to assess the robustness of the results. Results: Costs and health outcomes were lowest (€4,858 and 6.04 QALYs) for the 100% threshold, and highest (€10,939 and 6.21 QALYs) for the 2% threshold, respectively. The incremental cost effectiveness ratio for the 2%, 5%, 10%, and 20% threshold compared with the first threshold above (i.e., 5%, 10%, 20%, and 100%) were €189,222/QALY, €130,689/QALY, €51,920/QALY, and €23,187/QALY respectively. Applying a WTP threshold of €20.000 the probabilities for the 2%, 5%, 10%, 20%, and 100% threshold strategies being cost-effective were 0.0%, 0.3%, 4.9%, 30.3%, and 64.5% respectively. Conclusion: Applying a WTP threshold of €20.000, completely omitting ePLND in CaP patients is cost-effective compared to other risk-based strategies. However, applying a 20% threshold for probable LNI to the Briganti 2012 nomogram or the Memorial Sloan Kettering Cancer Center web-calculator, may be a feasible alternative, in particular when higher WTP values are considered