Psychometric Evaluation of a Patient-Reported Symptom Index for Nonmuscle Invasive Bladder Cancer: Field Testing Protocol
Bibliographic record
Abstract
BACKGROUND: Nonmuscle invasive bladder cancer (NMIBC) is a chronic condition requiring intensive follow-up, repeated endoscopic examinations, tumor resections, and intravesical treatments that can occur every 3 months for life. In this clinical context, patient-reported outcomes (PROs) are a critical concern for patients and their managing clinicians. PROs have enormous potential to be integral to treatment assessment and recommendations for NMIBC; however, current PRO measures are inadequate for NMIBC because they lack key NMIBC-specific symptoms and side effects associated with contemporary treatments. OBJECTIVE: The overarching aim of this study was to develop and evaluate a patient-reported symptom index (SI) for individuals with NMIBC (the NMIBC-SI) that is acceptable to patients; reliable, valid, and responsive to differences between contemporary treatments for NMIBC; and fit for purpose as an endpoint in clinical trials. METHODS: The NMIBC-SI will be evaluated in 2 field tests across a total of 3 years. Field test 1 is a cross-sectional study design involving 225 adult NMIBC patients recruited while undergoing active treatment or those who completed final treatment within the past week. Data collected include patient demographics, clinical features of the tumor, risk category, treatment type, comorbidity, and PROs. Field test 2 is a prospective longitudinal study involving 225 newly diagnosed NMIBC-SI patients. Clinical data and patient-completed questionnaires will be collected at 4 time points during treatment: before tumor resection, 1 week after resection, end-of-induction intravesical therapy, and 1-year follow-up. Standard psychometric tests will be performed to assess the reliability, validity, responsiveness, and clinical utility of the NMIBC-SI. RESULTS: Participant recruitment to field test 1 commenced in February 2017. Recruitment for field test 2 is planned to commence in January 2018. Final results are expected to be published in 2019. The NMIBC-SI will be freely available for use via registration. CONCLUSIONS: This study protocol contains detailed methods that will be used across multiple international sites. Phase 2 in the development of the NMIBC-SI will enable a comprehensive evaluation of its reliability, validity, and responsiveness to ensure that the NMIBC-SI is fit for purpose in clinical research and provides an evidence base for the ongoing improvement of future therapies for NMIBC. TRIAL REGISTRATION: ClinicalTrials.gov NCT03091764; http://clinicaltrials.gov/ct2/showNCT03091764 (Archived by WebCite at http://www.webcitation.org/6umBhQeNX).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".