Financial toxicity questionnaire (FIT): development and validation of the italian version (FITALY) in head and neck cancer patients undergoing multimodal curative treatment
Bibliographic record
Abstract
BACKGROUND: Financial toxicity from cancer treatments is rising as an important patient-reported outcome. Its relevance was first assessed in the context of privately financed healthcare system, where the financial hardship caused by out-of-pocket payments negatively affects survival, while fewer evidence exists on its role in countries where care is financed by the public health care system. Head and Neck Cancer (HNC) patients face an increased risk for financial toxicity due to multimodal treatment and relevant out of pocket costs. The aim of this study was to develop and validate an Italian version of the Canadian Financial Index of Toxicity (FIT) questionnaire, defined FITALY. METHODS: FIT questionnaire was translated through a forward-backward process by two investigators independently, and the process was reviewed by a certified medical scientific English native speaker. Once reached consensus upon Italian translation, two Health Economics experts were consulted to adapt the questionnaire to Italian socio-economic context. The FITALY questionnaire v1.0 hereby developed was anonymously administered to two consecutive groups of 30 patients who had received curative, multimodal treatment for HNC cancer at ASST Spedali Civili of Brescia, Italy. A cognitive debriefing form was simultaneously administered to ask patients to exclude recurring and redundant items and include new relevant items. RESULTS: The 14-item FITALY questionnaire provides a global evaluation of financial toxicity ranging from 0 to 100. The questionnaire is divided into 4 domains: financial burden (6 items), exploring the objective financial toxicity burden; financial distress (2 items), which refers to the psychological distress related to financial toxicity; out-of-pocket costs (4 items), which focus on medical expenses paid by the patient; and loss of productivity (2 items), that investigates the disease impact on both patient's and caregiver's job activity. CONCLUSIONS: Starting from the Canadian 9-item FIT questionnaire, we developed and validated the Italian 14-item FITALY questionnaire. Prospective application to a cohort of Italian HNC patients is ongoing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".