The Effect of Antifibrotic Treatment on Health-related Quality of Life in Idiopathic Pulmonary Fibrosis
Bibliographic record
Abstract
Abstract Rationale: In chronic diseases, health related quality of life (HRQoL) is important for the patient's well-being. In idiopathic pulmonary fibrosis (IPF), antifibrotic treatment is recommended to slow down disease progression but the impact of pharmacotherapy on HRQoL is less known.This is important, since antifibrotics have side effects and the potential to affect daily living. Our aim was to explore HRQoL in Swedish IPF patients and to study the impact of antifibrotic treatment over time. Methods: Patients in the Swedish IPF-registry between January 2014 and October 2021 with a King's Brief Interstitial Lung Disease questionnaire (KBILD) performed within 90 days from diagnosis and at a 12-month follow-up were included. A categorization into three groups based on treatment duration with antifibrotics was made: no treatment, treatment for less than six months and treatment for six months or more. Six months was chosen as a threshold for receiving full efficacy of the treatment. Demographics, KBILD total and domain scores at diagnosis and at follow-up were investigated. A change ≤-2 in KBILD scores was considered as minimal clinically important difference in deterioration. Results: Altogether 158 patients with IPF (mean (SD) age 71 years (7); 71.5 % male) were included. The mean scores for KBILD were 55.2 (11) for total, and 55.6 (16), 41.0 (19) and 68.2 (21) for psychological, breathlessness/activities and chest symptoms, respectively. Patients with lower scores at diagnosis were more likely to be treated during the following 12 months (mean (SD) total score 54.4 (11) vs 61.4 (11), p<0.05, for treated and nontreated patients, respectively). At 12 months, chest domain deteriorated significantly with a mean difference of -2.2 from diagnosis. Treatment for six months or more was associated with stabilization of the total and chest domains in comparison with no treatment and treatment for less than six months (OR (95%CI) 0.08 (0.01-0.83) and 0.14 (0.03-0.75) for deterioration in total and chest domains, respectively). Conclusions: At time of IPF diagnosis, HRQoL is affected, in particular the domain breathlessness and activities. Antifibrotic treatment may slow down the deterioration of HRQoL, especially the quality related to disease progression, which is reflected in the chest symptoms domain. Despite known side effects of antifibrotics, HRQoL may not be deteriorated by treatment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".