Publications by authors named "P Cislo"
Article Synopsis
- The FDA suggests using anchor-based methods and eCDF curves to determine meaningful changes in clinical outcomes, but they may yield differing results despite both using an anchor.
- A study was conducted using both repeated measures models and eCDF methods on real and simulated data sets with 688 patients, comparing estimates for meaningful within-patient change in a clinical outcome assessment.
- Results showed that model-based methods provided more precise and reliable estimates of meaningful change compared to eCDF, which had wider confidence intervals and greater variability, especially when analyzing clinical data.
Background: The NCCN/FACT Bladder Symptom Index-18 (NFBlSI-18) is a bladder cancer-specific instrument. We aimed to psychometrically evaluate the reliability and validity of NFBlSI-18 and estimate change thresholds for total, disease-related symptoms-physical (DRS-P), DRS-emotional (DRS-E), and function/well-being (F/WB) scales in patients with locally advanced/metastatic urothelial cancer (la/mUC).
Methods: JAVELIN Bladder 100 trial data were analyzed.
Determining clinically meaningful change (CMC) in a patient-reported (PRO) measure is central to its existence in gauging how patients feel and function, especially for evaluating a treatment effect. Anchor-based approaches are recommended to estimate a CMC threshold on a PRO measure. Determination of CMC involves linking changes or differences in the target PRO measure to that in an external (anchor) measure that is easier to interpret than and appreciably associated with the PRO measure.
View Article and Find Full Text PDFPatient-reported outcomes (PROs), such as symptoms, functioning, and other health-related quality-of-life concepts are gaining a more prominent role in the benefit-risk assessment of cancer therapies. However, varying ways of analysing, presenting, and interpreting PRO data could lead to erroneous and inconsistent decisions on the part of stakeholders, adversely affecting patient care and outcomes. The Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints in Cancer Clinical Trials-Innovative Medicines Initiative (SISAQOL-IMI) Consortium builds on the existing SISAQOL work to establish recommendations on design, analysis, presentation, and interpretation for PRO data in cancer clinical trials, with an expanded set of topics, including more in-depth recommendations for randomised controlled trials and single-arm studies, and for defining clinically meaningful change.
View Article and Find Full Text PDFObjectives: To have confidence in one's interpretation of treatment effects assessed by comparing trial results to external controls, minimizing bias is a critical step. We sought to investigate different methods for causal inference in simulated data sets with measured and unmeasured confounders.
Methods: The simulated data included three types of outcomes (continuous, binary, and time-to-event), treatment assignment, two measured baseline confounders, and one unmeasured confounding factor.