Background: Diffuse parenchymal lung disease represents a diverse and challenging group of pulmonary disorders. A consistent diagnostic approach to diffuse parenchymal lung disease is crucial if clinical trial data are to be applied to individual patients. We aimed to evaluate inter-multidisciplinary team agreement for the diagnosis of diffuse parenchymal lung disease.
Methods: We did a multicentre evaluation of clinical data of patients who presented to the interstitial lung disease unit of the Royal Brompton and Harefield NHS Foundation Trust (London, UK; host institution) and required multidisciplinary team meeting (MDTM) characterisation between March 1, 2010, and Aug 31, 2010. Only patients whose baseline clinical, radiological, and, if biopsy was taken, pathological data were undertaken at the host institution were included. Seven MDTMs, consisting of at least one clinician, radiologist, and pathologist, from seven countries (Denmark, France, Italy, Japan, Netherlands, Portugal, and the UK) evaluated cases of diffuse parenchymal lung disease in a two-stage process between Jan 1, and Oct 15, 2015. First, the clinician, radiologist, and pathologist (if lung biopsy was completed) independently evaluated each case, selected up to five differential diagnoses from a choice of diffuse lung diseases, and chose likelihoods (censored at 5% and summing to 100% in each case) for each of their differential diagnoses, without inter-disciplinary consultation. Second, these specialists convened at an MDTM and reviewed all data, selected up to five differential diagnoses, and chose diagnosis likelihoods. We compared inter-observer and inter-MDTM agreements on patient first-choice diagnoses using Cohen's kappa coefficient (κ). We then estimated inter-observer and inter-MDTM agreement on the probability of diagnosis using weighted kappa coefficient (κw). We compared inter-observer and inter-MDTM confidence of patient first-choice diagnosis. Finally, we evaluated the prognostic significance of a first-choice diagnosis of idiopathic pulmonary fibrosis (IPF) versus not IPF for MDTMs, clinicians, and radiologists, using univariate Cox regression analysis.
Findings: 70 patients were included in the final study cohort. Clinicians, radiologists, pathologists, and the MDTMs assigned their patient diagnoses between Jan 1, and Oct 15, 2015. IPF made up 88 (18%) of all 490 MDTM first-choice diagnoses. Inter-MDTM agreement for first-choice diagnoses overall was moderate (κ=0·50). Inter-MDTM agreement on diagnostic likelihoods was good for IPF (κw=0·71 [IQR 0·64-0·77]) and connective tissue disease-related interstitial lung disease (κw=0·73 [0·68-0·78]); moderate for non-specific interstitial pneumonia (NSIP; κw=0·42 [0·37-0·49]); and fair for hypersensitivity pneumonitis (κw=0·29 [0·24-0·40]). High-confidence diagnoses (>65% likelihood) of IPF were given in 68 (77%) of 88 cases by MDTMs, 62 (65%) of 96 cases by clinicians, and in 57 (66%) of 86 cases by radiologists. Greater prognostic separation was shown for an MDTM diagnosis of IPF than compared with individual clinician's diagnosis of this disease in five of seven MDTMs, and radiologist's diagnosis of IPF in four of seven MDTMs.
Interpretation: Agreement between MDTMs for diagnosis in diffuse lung disease is acceptable and good for a diagnosis of IPF, as validated by the non-significant greater prognostic separation of an IPF diagnosis made by MDTMs than the separation of a diagnosis made by individual clinicians or radiologists. Furthermore, MDTMs made the diagnosis of IPF with higher confidence and more frequently than did clinicians or radiologists. This difference is of particular importance, because accurate and consistent diagnoses of IPF are needed if clinical outcomes are to be optimised. Inter-multidisciplinary team agreement for a diagnosis of hypersensitivity pneumonitis is low, highlighting an urgent need for standardised diagnostic guidelines for this disease.
Funding: National Institute of Health Research, Imperial College London.
Copyright © 2016 Elsevier Ltd. All rights reserved.