Pulmonary Pathology Society Survey on Practice Approaches in the Histologic Diagnosis of Fibrotic Interstitial Lung Disease: Consensus and Opportunities
Bibliographic record
Abstract
CONTEXT.—: The pathologic diagnosis of usual interstitial pneumonia (UIP) remains a challenging area, and application of histologic UIP guidelines has proved difficult. OBJECTIVE.—: To understand current practice approaches by pulmonary pathologists for the histologic diagnosis of UIP and other fibrotic interstitial lung diseases (ILDs). DESIGN.—: The Pulmonary Pathology Society (PPS) ILD Working Group developed and sent a 5-part survey on fibrotic ILD electronically to the PPS membership. RESULTS.—: One hundred sixty-one completed surveys were analyzed. Of the respondents, 89% reported using published histologic features in clinical guidelines for idiopathic pulmonary fibrosis (IPF) in their pathologic diagnosis; however, there was variability in reporting terminology, quantity and quality of histologic features, and the use of guideline categorization. Respondents were very likely to have access to pulmonary pathology colleagues (79%), pulmonologists (98%), and radiologists (94%) to discuss cases. Half of respondents reported they may alter their pathologic diagnosis based on additional clinical and radiologic history if it is pertinent. Airway-centered fibrosis, granulomas, and types of inflammatory infiltrates were considered important, but there was poor agreement on how these features are defined. CONCLUSIONS.—: There is significant consensus among the PPS membership on the importance of histologic guidelines/features of UIP. There are unmet needs for (1) consensus and standardization of diagnostic terminology and incorporation of recommended histopathologic categories from the clinical IPF guidelines into pathology reports, (2) agreement on how to incorporate into the report relevant clinical and radiographic information, and (3) defining the quantity and quality of features needed to suggest alternative diagnoses.
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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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".