Sakata, Kenneth

Transbronchial cryobiopsies (CB) are increasingly replacing surgical biopsies (video-assisted thoracoscopic/VATS biopsies) for diagnosing diffuse parenchymal lung disease (interstitial lung disease, ILD), but there is very little guidance for pathologists on CB interpretation. Here we propose a fairly simple approach. First, if the diagnosis can be made on a traditional forceps biopsy, it can be made on a cryobiopsy. Many diseases with specific features will fall into this category (eg, sarcoidosis or Langerhans cell histiocytosis). More problematic are patterns such as usual interstitial pneumonia (UIP) or nonspecific interstitial pneumonia (NSIP), in which low-power architecture is the key to diagnosis. In this circumstance, an adequate sample is crucial to look for features such as fibroblast foci, because a combination of fibroblast foci plus any patchy old fibrosis, fibrotic architectural remodeling, or honeycombing, allows a diagnosis of a UIP pattern. However, in most instances, CB will not separate the UIP patterns seen in idiopathic pulmonary fibrosis, fibrotic hypersensitivity pneumonitis, or connective tissue disease-interstitial lung disease (CTD-ILD), although giant cells/granulomas (uncommon findings) in this setting favor fibrotic hypersensitivity pneumonitis. Fibroblast foci can be difficult to differentiate from organizing pneumonia (OP), but granulation tissue plugs clearly in airspaces favor OP. Absent fibroblast foci, patchy old fibrosis, architectural distortion, and honeycombing by themselves do not allow a specific diagnosis. NSIP in CB microscopically looks like NSIP in VATS biopsies, and the presence of an NSIP or an NSIP+OP pattern is typical of CTD-ILD. All the above diagnoses require correlation with clinical and radiologic findings.

ABSTRACT The health care-associated pneumonia (HCAP) criteria have a limited ability to predict pneumonia caused by drug-resistant bacteria and favor the overutilization of broad-spectrum antibiotics. We aimed to derive and validate a clinical prediction score with an improved ability to predict the risk of pneumonia due to drug-resistant pathogens compared to that of HCAP criteria. A derivation cohort of 200 microbiologically confirmed pneumonia cases in 2011 and 2012 was identified retrospectively. Risk factors for pneumonia due to drug-resistant pathogens were evaluated by logistic regression, and a novel prediction score (the drug resistance in pneumonia [DRIP] score) was derived. The score was then validated in a prospective, observational cohort of 200 microbiologically confirmed cases of pneumonia at four U.S. centers in 2013 and 2014. The DRIP score (area under the receiver operator curve [AUROC], 0.88 [95% confidence interval {CI}, 0.82 to 0.93]) performed significantly better ( P = 0.02) than the HCAP criteria (AUROC, 0.72 [95% CI, 0.64 to 0.79]). At a threshold of ≥4 points, the DRIP score demonstrated a sensitivity of 0.82 (95% CI, 0.67 to 0.88), a specificity of 0.81 (95% CI, 0.73 to 0.87), a positive predictive value (PPV) of 0.68 (95% CI, 0.56 to 0.78), and a negative predictive value (NPV) of 0.90 (95% CI, 0.81 to 0.93). By comparison, the performance of HCAP criteria was less favorable: sensitivity was 0.79 (95% CI, 0.67 to 0.88), specificity was 0.65 (95% CI, 0.56 to 0.73), PPV was 0.53 (95% CI, 0.42 to 0.63), and NPV was 0.86 (95% CI, 0.77 to 0.92). The overall accuracy of the HCAP criteria was 69.5% (95% CI, 62.5 to 75.7%), whereas that of the DRIP score was 81.5% (95% CI, 74.2 to 85.6%) ( P = 0.005). Unnecessary extended-spectrum antibiotics were recommended 46% less frequently by applying the DRIP score (25/200, 12.5%) than by use of HCAP criteria (47/200, 23.5%) ( P = 0.004), without increasing the rate at which inadequate treatment recommendations were made. The DRIP score was more predictive of the risk of pneumonia due to drug-resistant pathogens than HCAP criteria and may have the potential to decrease antibiotic overutilization in patients with pneumonia. Validation in larger cohorts of patients with pneumonia due to all causes is necessary.