The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Idiopathic Pulmonary Fibrosis: Relationship between Histopathologic Features and Mortality
Abstract
It is hypothesized that the extent and severity of fibrosis and cellularity found on lung biopsy determine the prognosis and response to therapy in idiopathic pulmonary fibrosis (IPF). The objective of this study was to determine which histopathologic features predict survival in IPF. We prospectively studied 87 patients with usual interstitial pneumonia (UIP) confirmed by surgical lung biopsy. Four pathologists independently graded the extent and severity of specific histopathologic features. We used Cox proportional-hazards models to assess the effect of histopathologic patterns on patients' survival. The effects of age, sex, and smoking were also included in the analysis. Sixty-three patients died during the 17-yr study period. Survival was longer in subjects with lesser degrees of granulation/connective tissue deposition (fibroblastic foci). The degree of alveolar space cellularity, alveolar wall fibrosis, and cellularity did not affect survival. A history of cigarette smoking, the level of dyspnea, and the degree of lung stiffness at presentation were also shown to be independent factors predicting survival. The extent of fibroblastic foci present on lung biopsy predicts survival in IPF. These findings support the hypothesis that the critical pathway to end-stage fibrosis is not "alveolitis" but rather the ongoing epithelial damage and repair process associated with persistent fibroblastic proliferation. Controlling these processes, rather than stopping inflammation, appears most important in preventing progressive disease and the fatal outcome common in IPF.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Johnston, I. D., Prescott, R. J., Chalmers, J. C., & Rudd, R. M. (1997) · Thorax · doi:10.1136/thx.52.1.38 · Cited by 205
Cited by
Raghu, G., Collard, H. R., Egan, J. J., Martinez, F. J., Behr, J., Brown, K. K., Colby, T. V., Cordier, J.-F., Flaherty, K. R., Lasky, J. A., et al. (2011) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.2009-040gl · Cited by 7,186
Self-citationClinical course and prediction of survival in idiopathic pulmonary fibrosis
Ley, B., Collard, H. R., & King, T. E. (2011) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201006-0894ci · Cited by 1,765
Self-citationTGF-β1 induces human alveolar epithelial to mesenchymal cell transition (EMT)
Kasai, H., Allen, J. T., Mason, R. M., Kamimura, T., & Zhang, Z. (2005) · Respiratory Research · doi:10.1186/1465-9921-6-56 · Cited by 744
Reversal of persistent fibrosis in aging by targeting Nox4-Nrf2 redox imbalance
Hecker, L., Logsdon, N. J., Kurundkar, D., Kurundkar, A., Bernard, K., Hock, T., Meldrum, E., Sanders, Y. Y., & Thannickal, V. J. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3008182 · Cited by 686
Königshoff, M., Kramer, M., Balsara, N., Wilhelm, J., Amarie, O. V., Jahn, A., Rose, F., Fink, L., Seeger, W., Schaefer, L., et al. (2009) · Journal of Clinical Investigation · doi:10.1172/jci33950 · Cited by 558
Metadata
- Authors
- KING, T. E., SCHWARZ, M. I., BROWN, K., TOOZE, J. A., COLBY, T. V., WALDRON, J. A., FLINT, A., THURLBECK, W., & CHERNIACK, R. M.
- Venue
- American Journal of Respiratory and Critical Care Medicine
- Publisher
- Oxford University Press (OUP)
- Published
- 2001-09-15
- Volume
- 164
- Issue
- 6
- Pages
- 1025-1032
- ISSN
- 1073-449X (ISSN-L)
- 1535-4970
- OpenAlex
- W2052397837
- Cited by
- 628
- References
- 2
- FWCI
- 22.06
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Idiopathic Pulmonary Fibrosis: Relationship between Histopathologic Features and Mortality. https://app.cochat.ai/papers/10.1164/ajrccm.164.6.2001056
- The paper
- KING, T. E., SCHWARZ, M. I., BROWN, K., TOOZE, J. A., COLBY, T. V., WALDRON, J. A., FLINT, A., THURLBECK, W., & CHERNIACK, R. M. (2001). Idiopathic Pulmonary Fibrosis: Relationship between Histopathologic Features and Mortality. American Journal of Respiratory and Critical Care Medicine. https://doi.org/10.1164/ajrccm.164.6.2001056
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.