Fujimoto, Kiminori

AimVarious factors are underlying for the onset of non‐B, non‐C hepatitis virus‐related hepatocellular carcinoma (NBNC‐HCC). We aimed to investigate the independent risk factors and profiles associated with NBNC‐HCC using a data‐mining technique.MethodsWe conducted a case‐control study and enrolled 223 NBNC‐HCC patients and 669 controls from a health checkup database (n = 176 886). Multivariate analysis, random forest analysis and a decision‐tree algorithm were employed to examine the independent risk factors, factors distinguishing between the case and control groups, and to identify profiles for the incidence of NBNC‐HCC, respectively.ResultsIn multivariate analysis, besides γ‐glutamyltransferase (GGT) levels and the Brinkman index, albumin level was an independent negative risk factor for the incidence of NBNC‐HCC (odds ratio = 0.67; 95% confidence interval = 0.60–0.70; P < 0.0001). In random forest analysis, serum albumin level was the highest‐ranked variable for distinguishing between the case and control groups (98 variable importance). A decision‐tree algorithm was created for albumin and GGT levels, the aspartate aminotransferase‐to‐platelet ratio index (APRI) and the Brinkman index. The serum albumin level was selected as the initial split variable, and 82.5% of the subjects with albumin levels of less than 4.01 g/dL were found to have NBNC‐HCC.ConclusionData‐mining analysis revealed that serum albumin level is an independent risk factor and the most distinguishable factor associated with the incidence of NBNC‐HCC. Furthermore, we created an NBNC‐HCC profile consisting of albumin and GGT levels, the APRI and the Brinkman index. This profile could be used in the screening strategy for NBNC‐HCC.

AbstractBackground and objectiveDespite significant recent progress in the understanding of idiopathic pulmonary fibrosis (IPF), the early phase of the disease is still poorly understood. We studied patients with IPF without pulmonary function impairment in order to determine the clinical features, natural history and key findings for physiological progression.MethodsTwenty‐five patients without pulmonary function impairment were identified from among patients with previously diagnosed IPF who underwent surgical lung biopsies between January 1997 and December 2006 at our institutions. ‘Without pulmonary function impairment’ was defined as both forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLco) >80% predicted. Patients diagnosed with IPF through multidisciplinary discussion based on the new IPF guidelines were the subjects of this study.ResultsSixteen patients had a confirmed diagnosis of IPF. Eleven patients presented with chest X‐ray abnormality found during an annual health examination. Seven patients were asymptomatic. Eleven patients showed physiological disease progression (median time; 19.9 ± 12.3 months) defined by a decline of at least 10% in FVC or at least 15% in DLco. Univariate analysis revealed that both usual interstitial pneumonia pattern and extent of honeycombing on high‐resolution computed tomography (HRCT) were factors associated with disease progression (odds ratio 5.634, 95% confidence interval 1.364–23.278; odds ratio 2.371/5%, 95% confidence interval 1.042–5.395).ConclusionsIPF patients without pulmonary function impairment have a progressive but slow clinical course. The existence and extent of honeycombing on HRCT are predictive of disease progression.

Abstract Rationale Patients with a clinicopathological diagnosis of idiopathic pulmonary fibrosis (IPF) may have typical findings of usual interstitial pneumonia (UIP) on computed tomography (CT) or nonspecific or atypical findings, including those often seen in nonspecific interstitial pneumonia. Objectives The aims of this study were to revisit the high-resolution CT findings of IPF and to clarify the correlation between the CT findings and mortality. Methods The study included 98 patients with a histologic diagnosis of UIP and a clinical diagnosis of IPF. Two observers evaluated the CT findings independently and classified each case into one of the following three categories: (1) definite UIP, (2) consistent with UIP, or (3) suggestive of alternative diagnosis. The correlation between the CT categories and mortality was evaluated using the Kaplan-Meier method and the log-rank test, as well as Cox proportional hazards regression models. Measurements and Main Results Thirty-three of the 98 CT scans were classified as definite UIP, 36 as consistent with UIP, 29 as suggestive of an alternative diagnosis. The mean survival was 45.7, 57.9, and 76.9 months, respectively. There was no significant difference in survival among the three categories (all P &gt; 0.05). Traction bronchiectasis and fibrosis scores were significant predictors of outcome (hazard ratios: 1.30 and 1.10, respectively; 95% confidence intervals: 1.18–14.2 and 1.03–1.19, respectively). Conclusions In patients with IPF and UIP pattern on the biopsy, the pattern of abnormality on thin-section CT, whether characteristic of UIP or suggestive of alternative diagnosis, does not influence prognosis. Prognosis is influenced by traction bronchiectasis and fibrosis scores.