Algorithms Identifying Patients With Acute Exacerbation of Interstitial Pneumonia and Acute Interstitial Lung Diseases Developed Using Japanese Administrative Data.

BACKGROUND: We aimed to develop algorithms to identify patients with acute exacerbation of interstitial pneumonia and acute interstitial lung diseases using Japanese administrative data. METHODS: This single-center validation study examined diagnostic algorithm accuracies. We included patients >18 years old with at least one claim that was a candidate for acute exacerbation of interstitial pneumonia, acute interstitial lung diseases, and pulmonary alveolar hemorrhage who were admitted to our hospital between January 2016 and December 2021. Diagnoses of these conditions were confirmed by at least two respiratory physicians through a chart review. The positive predictive value was calculated for the created algorithms. RESULTS: Of the 1,109 hospitalizations analyzed, 285 and 243 were for acute exacerbation of interstitial pneumonia and acute interstitial lung diseases, respectively. As there were only five cases of pulmonary alveolar hemorrhage, we decided not to develop an algorithm for it. For acute exacerbation of interstitial pneumonia, acute interstitial lung diseases, and acute exacerbation of interstitial pneumonia or acute interstitial lung diseases, algorithms with high positive predictive value (0.82, 95% confidence interval: 0.76-0.86; 0.82, 0.74-0.88; and 0.89, 0.85-0.92, respectively) and algorithms with slightly inferior positive predictive value but more true positives (0.81, 0.75-0.85; 0.77, 0.71-0.83; and 0.85, 0.82-0.88, respectively) were developed. CONCLUSION: We developed algorithms with high positive predictive value for identifying patients with acute exacerbation of interstitial pneumonia and acute interstitial lung diseases, useful for future database studies on such patients using Japanese administrative data.

Clinical phenotypes from fatal cases of acute respiratory distress syndrome caused by pneumonia.

There have been no report of objective clinical characteristics or prognostic factors that predict fatal outcome of acute respiratory distress syndrome (ARDS) since the Berlin definition was published. The aim of this study is to identify clinically available predictors that distinguish between two phenotypes of fatal ARDS due to pneumonia. In total, 104 cases of Japanese patients with pneumonia-induced ARDS were extracted from our prospectively collected database. Fatal cases were divided into early (< 7 days after diagnosis) and late (≥ 7 days) death groups, and clinical variables and prognostic factors were statistically evaluated. Of the 50 patients who died within 180 days, 18 (36%) and 32 (64%) were in the early (median 2 days, IQR [1, 5]) and late (median 16 days, IQR [13, 29]) death groups, respectively. According to multivariate regression analyses, the APACHE II score (HR 1.25, 95%CI 1.12-1.39, p < 0.001) and the disseminated intravascular coagulation score (HR 1.54, 95%CI 1.15-2.04, p = 0.003) were independent prognostic factors for early death. In contrast, late death was associated with high-resolution computed tomography (HRCT) score indicating early fibroproliferation (HR 1.28, 95%CI 1.13-1.42, p < 0.001) as well as the disseminated intravascular coagulation score (HR 1.24, 95%CI 1.01-1.52, p = 0.039). The extent of fibroproliferation on HRCT, and the APACHE II scores along with coagulation abnormalities, should be considered for use in predictive enrichment and personalized medicine for patients with ARDS due to pneumonia.

The effects of switching EGFR-TKI treatments for non-small cell lung cancer because of adverse events.

BACKGROUND: Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are used to treat patients with non-small cell lung cancer (NSCLC) and EGFR driver mutations. Although some patients discontinued these treatments because of adverse events, it is unclear whether switching EGFR-TKI because of adverse events provides a benefit. METHODS: This retrospective study evaluated data from 22 patients with EGFR mutation-positive NSCLC who received at least two EGFR-TKIs that were switched because of adverse events (March 2011 to September 2017). Progression-free survival 2 (PFS2) was defined as the time from starting of the first EGFR-TKI treatment to disease progression during the second EGFR-TKI treatment. RESULTS: Seventeen patients received gefitinib as the first EGFR-TKI treatment, while four patients received afatinib and one patient received erlotinib. The median time to failure of the first EGFR-TKI treatment was 1.6 months. The EGFR-TKIs were switched because of hepatotoxicity (n = 16), interstitial lung disease (n = 3), and other reasons (n = 3). The median washout period was 1.1 months. Seventeen patients received erlotinib as the second EGFR-TKI treatment, while three patients received gefitinib and two patients received afatinib. The median PFS for the second EGFR-TKI treatment was 15.2 months. The median PFS2 was 17.7 months and the median overall survival was 32.8 months. CONCLUSIONS: Switching EGFR-TKIs because of adverse events provided a clinical benefit for patients with EGFR mutation-positive NSCLC. Appropriate judgment regarding switching from one EGFR-TKI to another may improve the performance status and prognosis of patients with EGFR mutation-positive NSCLC.

The association between tumor burden and severe immune-related adverse events in non-small cell lung cancer patients responding to immune-checkpoint inhibitor treatment.

OBJECTIVES: The use of immune checkpoint inhibitors (ICIs) for advanced non-small cell lung cancer (NSCLC) has demonstrated survival benefits, although some treatment responders (defined as patients with non-progressive disease) are forced to discontinue treatment because of severe immune-related adverse events (irAEs). An association between treatment efficacy and irAEs has been reported. However, it is unclear which treatment responders are likely to develop severe irAEs. We aimed to examine risk factors for ICI-related severe irAEs in patients with NSCLC. MATERIALS AND METHODS: Between February 2016 and October 2018, we retrospectively evaluated 42 patients with NSCLC at our institution who responded to ICI treatment. Tumor burden was measured as the sum of the unidimensional diameters of up to five target lesions, according to the Response Evaluation Criteria in Solid Tumors version 1.1. RESULTS: ICIs were discontinued in 15 of 42 treatment responders because of severe irAEs. Tumor burden was a significant independent predictor of severe irAEs (p = 0.03). The odds ratio of severe irAEs and tumor burden over 90 mm was 8.62 (95% confidence interval = 1.96-37.9, p = 0.004). CONCLUSION: A high tumor burden was a risk factor for severe irAEs in patients with NSCLC who responded to ICI treatment.