Outcomes of Patients With Interstitial Lung Disease Receiving Programmed Cell Death 1 Inhibitors: A Retrospective Case Series
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Immune checkpoint inhibitors (ICIs), such as programmed cell death 1 (PD-1) inhibitors, are used to treat multiple cancers. Limited data exist as to the use of ICIs in patients with coexistent interstitial lung disease (ILD). We conducted a retrospective case series to assess clinical and radiologic outcomes of patients with ILD treated with PD-1 inhibitors. METHODS: Eligible patients were 18 years of age or older, treated with pembrolizumab or nivolumab for oncologic indications, and had evidence of ILD on chest computed tomography scan not attributable to radiotherapy before initiation of ICI therapy. Outcomes of interest included mortality, hospitalizations for respiratory-related causes, development of pneumonitis, and radiologic change in ILD over a 1-year follow-up period. RESULTS: We included 41 patients in the analysis. At 1 year, 17 patients (41.5%) were alive, 23 had died (56.1%), and 1 (2.4%) was lost to follow-up. Of 23 deaths, 16 (69.6%) were due to cancer, 4 (17.4%) to causes excluding cancer and ILD, and 3 (13.0%) to hypoxemic respiratory failure from ILD- or ICI-induced pneumonitis. Three patients (7.3%) required hospitalization owing to ILD, including drug-induced pneumonitis, and 3 (7.3%) developed pneumonitis attributable to anti-PD-1 therapy. On follow-up computed tomography scans, 32 patients (78.0%) had stable or improved ILD and 9 (22.0%) had progression. CONCLUSION: Patients with ILD receiving PD-1 inhibitors more frequently died of cancer-related causes than from ILD. Further research is needed to determine the safety of ICIs in patients with ILD and if ILD subtype may help to refine ICI-associated risks.
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.
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) | 0.001 | 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 it