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Medical diagnostic tests are used to classify subjects as non-diseased or diseased. The classification rule usually consists of classifying subjects using the values of a continuous marker that is dichotomised by means of a threshold. Here, the optimum threshold estimate is found by minimising a cost function that accounts for both decision costs and sampling uncertainty. The cost function is optimised either analytically in a normal distribution setting or empirically in a free-distribution setting when the underlying probability distributions of diseased and non-diseased subjects are unknown. Inference of the threshold estimates is based on approximate analytically standard errors and bootstrap-based approaches. The performance of the proposed methodology is assessed by means of a simulation study, and the sample size required for a given confidence interval precision and sample size ratio is also calculated. Finally, a case example based on previously published data concerning the diagnosis of Alzheimer's patients is provided in order to illustrate the procedure.

During chemotherapy, bone marrow stem cells that produce white blood cells, red blood cells, and platelets can be damaged, resulting in myelosuppression. Adding trilaciclib prior to chemotherapy reduces myelosuppression and the need for rescue interventions and improves patient quality of life, with no impact on antitumor efficacy. Background: Chemotherapy-induced myelosuppression (CIM) and its sequalae cause significant side effects and harm to quality of life. Trilaciclib is an intravenous CDK4/6 inhibitor that is administered prior to chemotherapy to protect hematopoietic stem and progenitor cells from chemotherapy-induced damage (myeloprotection). Patients and Methods: Data from three randomized, double-blind, placebo-controlled studies (NCT02499770, NCT03041311, and NCT02514447) were pooled to evaluate the effects of trilaciclib administered prior to standard-of-care chemotherapy (first-line etoposide plus carboplatin [E/P], first-line E/P plus atezolizumab, and second-/third-line topotecan) in patients with extensive-stage small cell lung cancer (ES-SCLC). The primary endpoints were duration of severe neutropenia (absolute neutrophil count < 0.5 × 10 9 cells/L) in cycle 1 and occurrence of severe neutropenia. Additional prespecified endpoints further assessed the effect of trilaciclib on myeloprotection, health-related quality of life (HRQoL), antitumor efficacy, and safety. Results: Of 242 randomized patients, 123 received trilaciclib and 119 received placebo. Compared with placebo, administration of tr ilaciclib pr ior to chemotherapy resulted in significant decreases in most measures of multilineage CIM. The reduction in hematologic toxicity translated into the reduced need for supportive care interventions and hospitalizations due to CIM or sepsis and improvements in HRQoL domains related to the protected cell lineages,

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In the diagnostic area, the usual setting considers two populations: nondiseased and diseased. The use of the standard ROC analysis methodology is well established. Sometimes, however, diagnostic problems inherently include more than two classification states. For example, 'yes, uncertain, no' or 'low, normal, high'. Here we consider a three-normal distribution setting and derive estimators for the optimum thresholds between states based on a cost function. These estimators can be extended for clinical contexts with more than three states. This approach is well known for the two-state setting and its advantage lies in the fact that it accounts for the specific context's properties, such as disease prevalence and classification costs. Here we calculated the variance of the estimators by the use of parametric methods on nonlinear equations and we constructed confidence intervals accounting for possible uncertainty in the threshold estimation. We conducted a simulation study to assess the performance of these estimators and the confidence intervals. Comparisons with the naive threshold estimation method of joining the distributions two-by-two and applying standard ROC techniques proved that the latter method is not reliable for all parameter combinations and should be avoided.