Prognostic implication of 1-year decline in diffusing capacity in newly diagnosed idiopathic pulmonary fibrosis.

The progression of idiopathic pulmonary fibrosis (IPF) is assessed through serial monitoring of forced vital capacity (FVC). Currently, data regarding the clinical significance of longitudinal changes in diffusing capacity for carbon monoxide (DLCO) is lacking. We investigated the prognostic implications of a 1-year decline in DLCO in 319 patients newly diagnosed with IPF at a tertiary hospital between January 2010 and December 2020. Changes in FVC and DLCO over the first year after the initial diagnosis were reviewed; a decline in FVC ≥ 5% and DLCO ≥ 10% predicted were considered significant changes. During the first year after diagnosis, a significant decline in FVC and DLCO was observed in 101 (31.7%) and 64 (20.1%) patients, respectively. Multivariable analysis showed that a 1-year decline in FVC ≥ 5% predicted (aHR 2.74, 95% CI 1.88-4.00) and 1-year decline in DLCO ≥ 10% predicted (aHR 2.31, 95% CI 1.47-3.62) were independently associated with a higher risk of subsequent mortality. The prognostic impact of a decline in DLCO remained significant regardless of changes in FVC, presence of emphysema, or radiographic indications of pulmonary hypertension. Therefore, serial monitoring of DLCO should be recommended because it may offer additional prognostic information compared with monitoring of FVC alone.

Performance of the Galactomannan Test for the Diagnosis of Invasive Pulmonary Aspergillosis using Non-invasive Proximal Airway Samples.

OBJECTIVE: To diagnose invasive pulmonary aspergillosis (IPA), galactomannan (GM) detection in serum or bronchoalveolar lavage fluid (BALF) is widely used. However, the utility of proximal airway GM test (from induced sputum or tracheal aspirate) has not been well elucidated. METHODS: In this retrospective cohort study, we evaluated the diagnostic performance of proximal airway GM in diagnosis of IPA including COVID-19 associated pulmonary aspergillosis (CAPA). Between January 2022 and January 2023, patients who had been tested for GM with clinical suspicion or for surveillance from any specimen (serum, induced sputum, tracheal aspirate, and BALF) were screened. IPA was diagnosed using EORTC/MSGERC criteria, and CAPA was diagnosed following the 2020 ECMM/ISHAM consensus criteria. RESULTS: Of 624 patients with GM results, 70 met the criteria for proven/probable IPA and 427 had no IPA. The others included possible IPA and chronic form of aspergillosis. The sensitivities and specificities of serum, proximal airway, and BALF GM for proven/probable IPA versus no IPA were 78.9% and 70.6%, 93.1% and 78.7%, and 78.6% and 91.0%, respectively. Areas under the receiver operating characteristic curve (AUCs) were 0.742 for serum GM, 0.935 for proximal airway GM, and 0.849 for BALF GM (serum GM vs proximal airway GM, p = 0.014; proximal airway GM vs BALF GM, p = 0.334; serum GM vs BALF GM, p = 0.286). CONCLUSION: This study demonstrates that the performance of GM test from non-invasive proximal airway samples is comparable or even better than those from serum and distal airway sample (BALF).

Reduced toxicity (FluBu3) versus myeloablative (BuCy) conditioning in acute myeloid leukemia patients who received first allogeneic hematopoietic stem cell transplantation in measurable residual disease-negative CR1.

In the present study, reduced toxicity (FluBu3) and myeloablative (BuCy) conditioning were compared in patients with AML who received first allogeneic HSCT in MRD-negative CR1. The study included 124 adult patients who underwent HSCT from an HLA-matched (8/8) sibling, unrelated, or 1-locus mismatched (7/8) unrelated donor (MMUD). The median age was 45 years and intermediate cytogenetics comprised majority (71.8%). The 2-year OS, RFS, CIR and NRM for BuCy (n = 78, 62.9%) and FluBu3 (n = 46, 37.1%) groups were 78.3% and 84.5% (p = 0.358), 78.0% and 76.3% (p = 0.806), 7.7% and 21.5% (p = 0.074) and 14.3% and 2.2% (p = 0.032), respectively. At the time of data cut-off, relapse and NRM were the main causes of HSCT failure in each of the FluBu3 and BuCy arms. Among patients, 75% of relapsed FluBu3 patients had high-risk features of either poor cytogenetics or FLT3-ITD mutation compared with 16.7% of BuCy patients. The majority of NRM in the BuCy group was due to GVHD (73%), half of whom received MMUD transplantation. To conclude, the FluBu3 reduced toxicity conditioning showed comparable post-transplant OS and RFS to BuCy and was associated with significantly reduced NRM that was offset by a trend towards higher risk of relapse even in MRD-negative CR1 population.

Measurement Variability of Same-Day CT Quantification of Interstitial Lung Disease: A Multicenter Prospective Study.

Purpose To investigate quantitative CT (QCT) measurement variability in interstitial lung disease (ILD) on the basis of two same-day CT scans. Materials and Methods Participants with ILD were enrolled in this multicenter prospective study between March and October 2022. Participants underwent two same-day CT scans at an interval of a few minutes. Deep learning-based texture analysis software was used to segment ILD features. Fibrosis extent was defined as the sum of reticular opacity and honeycombing cysts. Measurement variability between scans was assessed with Bland-Altman analyses for absolute and relative differences with 95% limits of agreement (LOA). The contribution of fibrosis extent to variability was analyzed using a multivariable linear mixed-effects model while adjusting for lung volume. Eight readers assessed ILD fibrosis stability with and without QCT information for 30 randomly selected samples. Results Sixty-five participants were enrolled in this study (mean age, 68.7 years ± 10 [SD]; 47 [72%] men, 18 [28%] women). Between two same-day CT scans, the 95% LOA for the mean absolute and relative differences of quantitative fibrosis extent were -0.9% to 1.0% and -14.8% to 16.1%, respectively. However, these variabilities increased to 95% LOA of -11.3% to 3.9% and -123.1% to 18.4% between CT scans with different reconstruction parameters. Multivariable analysis showed that absolute differences were not associated with the baseline extent of fibrosis (P = .09), but the relative differences were negatively associated (ß = -0.252, P < .001). The QCT results increased readers' specificity in interpreting ILD fibrosis stability (91.7% vs 94.6%, P = .02). Conclusion The absolute QCT measurement variability of fibrosis extent in ILD was 1% in same-day CT scans. Keywords: CT, CT-Quantitative, Thorax, Lung, Lung Diseases, Interstitial, Pulmonary Fibrosis, Diagnosis, Computer Assisted, Diagnostic Imaging Supplemental material is available for this article. © RSNA, 2024.

Effect of smoking on the diagnostic results and complication rates of percutaneous transthoracic needle biopsy.

OBJECTIVE: To investigate the association of smoking with the outcomes of percutaneous transthoracic needle biopsy (PTNB). METHODS: In total, 4668 PTNBs for pulmonary lesions were retrospectively identified. The associations of smoking status (never, former, current smokers) and smoking intensity (≤ 20, 21-40, > 40 pack-years) with diagnostic results (malignancy, non-diagnostic pathologies, and false-negative results in non-diagnostic pathologies) and complications (pneumothorax and hemoptysis) were assessed using multivariable logistic regression analysis. RESULTS: Among the 4668 PTNBs (median age of the patients, 66 years [interquartile range, 58-74]; 2715 men), malignancies, non-diagnostic pathologies, and specific benign pathologies were identified in 3054 (65.4%), 1282 (27.5%), and 332 PTNBs (7.1%), respectively. False-negative results for malignancy occurred in 20.5% (236/1153) of non-diagnostic pathologies with decidable reference standards. Current smoking was associated with malignancy (adjusted odds ratio [OR], 1.31; 95% confidence interval [CI]: 1.02-1.69; p = 0.03) and false-negative results (OR, 2.64; 95% CI: 1.32-5.28; p = 0.006), while heavy smoking (> 40 pack-years) was associated with non-diagnostic pathologies (OR, 1.69; 95% CI: 1.19-2.40; p = 0.003) and false-negative results (OR, 2.12; 95% CI: 1.17-3.92; p = 0.02). Pneumothorax and hemoptysis occurred in 21.8% (1018/4668) and 10.6% (495/4668) of PTNBs, respectively. Heavy smoking was associated with pneumothorax (OR, 1.33; 95% CI: 1.01-1.74; p = 0.04), while heavy smoking (OR, 0.64; 95% CI: 0.40-0.99; p = 0.048) and current smoking (OR, 0.64; 95% CI: 0.42-0.96; p = 0.04) were inversely associated with hemoptysis. CONCLUSION: Smoking history was associated with the outcomes of PTNBs. Current and heavy smoking increased false-negative results and changed the complication rates of PTNBs. CLINICAL RELEVANCE STATEMENT: Smoking status and intensity were independently associated with the outcomes of PTNBs. Non-diagnostic pathologies should be interpreted cautiously in current or heavy smokers. A patient's smoking history should be ascertained before PTNB to predict and manage complications. KEY POINTS: • Smoking status and intensity might independently contribute to the diagnostic results and complications of PTNBs. • Current and heavy smoking (> 40 pack-years) were independently associated with the outcomes of PTNBs. • Operators need to recognize the association between smoking history and the outcomes of PTNBs.

Association between body fat decrease during the first year after diagnosis and the prognosis of idiopathic pulmonary fibrosis: CT-based body composition analysis.

BACKGROUND: The prognostic role of changes in body fat in patients with idiopathic pulmonary fibrosis (IPF) remains underexplored. We investigated the association between changes in body fat during the first year post-diagnosis and outcomes in patients with IPF. METHODS: This single-center, retrospective study included IPF patients with chest CT scan and pulmonary function test (PFT) at diagnosis and a one-year follow-up between January 2010 and December 2020. The fat area (cm2, sum of subcutaneous and visceral fat) and muscle area (cm2) at the T12-L1 level were obtained from chest CT images using a fully automatic deep learning-based software. Changes in the body composition were dichotomized using thresholds dividing the lowest quartile and others, respectively (fat area: -52.3 cm2, muscle area: -7.4 cm2). Multivariable Cox regression analyses adjusted for PFT result and IPF extent on CT images and the log-rank test were performed to assess the association between the fat area change during the first year post-diagnosis and the composite outcome of death or lung transplantation. RESULTS: In total, 307 IPF patients (69.3 ± 8.1 years; 238 men) were included. During the first year post-diagnosis, fat area, muscle area, and body mass index (BMI) changed by -15.4 cm2, -1 cm2, and - 0.4 kg/m2, respectively. During a median follow-up of 47 months, 146 patients had the composite outcome (47.6%). In Cox regression analyses, a change in the fat area < -52.3 cm2 was associated with composite outcome incidence in models adjusted with baseline clinical variables (hazard ratio [HR], 1.566, P = .022; HR, 1.503, P = .036 in a model including gender, age, and physiology [GAP] index). This prognostic value was consistent when adjusted with one-year changes in clinical variables (HR, 1.495; P = .030). However, the change in BMI during the first year was not a significant prognostic factor (P = .941). Patients with a change in fat area exceeding this threshold experienced the composite outcome more frequently than their counterparts (58.4% vs. 43.9%; P = .007). CONCLUSION: A ≥ 52.3 cm2 decrease in fat area, automatically measured using deep learning technique, at T12-L1 in one year post-diagnosis was an independent poor prognostic factor in IPF patients.

Usual Interstitial Pneumonia: Associations With Complications After Percutaneous Transthoracic Needle Lung Biopsy.

BACKGROUND. Changes in lung parenchyma elasticity in usual interstitial pneumonia (UIP) may increase the risk for complications after percutaneous transthoracic needle biopsy (PTNB) of the lung. OBJECTIVE. The purpose of this article was to investigate the association of UIP findings on CT with complications after PTNB, including pneumothorax, pneumothorax requiring chest tube insertion, and hemoptysis. METHODS. This retrospective single-center study included 4187 patients (mean age, 63.8 ± 11.9 [SD] years; 2513 men, 1674 women) who underwent PTNB between January 2010 and December 2015. Patients were categorized into a UIP group and non-UIP group by review of preprocedural CT. In the UIP group, procedural CT images were reviewed to assess for traversal of UIP findings by needle. Multivariable logistic regression analyses were performed to identify associations between the UIP group and needle traversal with postbiopsy complications, controlling for a range of patient, lesion, and procedural characteristics. RESULTS. The UIP and non-UIP groups included 148 and 4039 patients, respectively; in the UIP group, traversal of UIP findings by needle was observed in 53 patients and not observed in 95 patients. The UIP group, in comparison with the non-UIP group, had a higher frequency of pneumothorax (35.1% vs 17.9%, p < .001) and pneumothorax requiring chest tube placement (6.1% vs 1.5%, p = .001) and lower frequency of hemoptysis (2.0% vs 6.1%, p = .03). In multivariable analyses, the UIP group with traversal of UIP findings by needle, relative to the non-UIP group, showed independent associations with pneumothorax (OR, 5.25; 95% CI, 2.94-9.37; p < .001) and pneumothorax requiring chest tube placement (OR, 9.55; 95% CI, 3.74-24.38; p < .001). The UIP group without traversal of UIP findings by needle, relative to the non-UIP group, was not independently associated with pneumothorax (OR, 1.18; 95% CI, 0.71-1.97; p = .51) or pneumothorax requiring chest tube placement (OR, 1.08; 95% CI, 0.25-4.72; p = .92). The UIP group, with or without traversal of UIP findings by needle, was not independently associated with hemoptysis. No patient experienced air embolism or procedure-related death. CONCLUSION. Needle traversal of UIP findings is a risk factor for pneumothorax and pneumothorax requiring chest tube placement after PTNB. CLINICAL IMPACT. When performing PTNB in patients with UIP, radiologists should plan a needle trajectory that does not traverse UIP findings, when possible.

Prognostic value of CT-defined ground-glass opacity in early-stage lung adenocarcinomas: a single-center study and meta-analysis.

OBJECTIVES: The prognostic value of ground-glass opacity at preoperative chest CT scans in early-stage lung adenocarcinomas is a matter of debate. We aimed to clarify the existing evidence through a single-center, retrospective cohort study and to quantitatively summarize the body of literature by conducting a meta-analysis. METHODS: In a retrospective cohort study, patients with clinical stage I lung adenocarcinoma were identified, and the prognostic value of ground-glass opacity was analyzed using multivariable Cox regression. Commercial artificial intelligence software was adopted as the second reader for the presence of ground-glass opacity. The primary end points were freedom from recurrence (FFR) and lung cancer-specific survival (LCSS). In a meta-analysis, we systematically searched Embase and OVID-MEDLINE up to December 30, 2021, for the studies based on the eighth-edition staging system. The pooled hazard ratios (HRs) of solid nodules (i.e., absence of ground-glass opacity) for various end points were calculated with a multi-level random effects model. RESULTS: In a cohort of 612 patients, solid nodules were associated with worse outcomes for FFR (adjusted HR, 1.98; 95% CI: 1.17-3.51; p = 0.01) and LCSS (adjusted HR, 1.937; 95% CI: 1.002-4.065; p = 0.049). The artificial intelligence assessment and multiple sensitivity analyses revealed consistent results. The meta-analysis included 13 studies with 12,080 patients. The pooled HR of solid nodules was 2.13 (95% CI: 1.69-2.67; I2 = 30.4%) for overall survival, 2.45 (95% CI: 1.52-3.95; I2 = 0.0%) for FFR, and 2.50 (95% CI: 1.28-4.91; I2 = 30.6%) for recurrence-free survival. CONCLUSIONS: The absence of ground-glass opacity in early-stage lung adenocarcinomas is associated with worse postoperative survival. CLINICAL RELEVANCE STATEMENT: Early-stage lung adenocarcinomas manifesting as solid nodules at preoperative chest CT, which indicates the absence of ground-glass opacity, were associated with poor postoperative survival. There is room for improvement of the clinical T categorization in the next edition staging system. KEY POINTS: • In a retrospective study of 612 patients with stage I lung adenocarcinoma, solid nodules were associated with shorter freedom from recurrence (adjusted hazard ratio [HR], 1.98; p = 0.01) and lung cancer-specific survival (adjusted HR, 1.937; p = 0.049). • Artificial intelligence-assessed solid nodules also showed worse prognosis (adjusted HR for freedom from recurrence, 1.94 [p = 0.01]; adjusted HR for lung cancer-specific survival, 1.93 [p = 0.04]). • In meta-analyses, the solid nodules were associated with shorter freedom from recurrence (HR, 2.45) and shorter overall survival (HR, 2.13).

Diagnostic performance and prognostic value of CT-defined visceral pleural invasion in early-stage lung adenocarcinomas.

OBJECTIVES: To analyze the diagnostic performance and prognostic value of CT-defined visceral pleural invasion (CT-VPI) in early-stage lung adenocarcinomas. METHODS: Among patients with clinical stage I lung adenocarcinomas, half of patients were randomly selected for a diagnostic study, in which five thoracic radiologists determined the presence of CT-VPI. Probabilities for CT-VPI were obtained using deep learning (DL). Areas under the receiver operating characteristic curve (AUCs) and binary diagnostic measures were calculated and compared. Inter-rater agreement was assessed. For all patients, the prognostic value of CT-VPI by two radiologists and DL (using high-sensitivity and high-specificity cutoffs) was investigated using Cox regression. RESULTS: In 681 patients (median age, 65 years [interquartile range, 58-71]; 382 women), pathologic VPI was positive in 130 patients. For the diagnostic study (n = 339), the pooled AUC of five radiologists was similar to that of DL (0.78 vs. 0.79; p = 0.76). The binary diagnostic performance of radiologists was variable (sensitivity, 45.3-71.9%; specificity, 71.6-88.7%). Inter-rater agreement was moderate (weighted Fleiss κ, 0.51; 95%CI: 0.43-0.55). For overall survival (n = 680), CT-VPI by radiologists (adjusted hazard ratio [HR], 1.27 and 0.99; 95%CI: 0.84-1.92 and 0.63-1.56; p = 0.26 and 0.97) or DL (HR, 1.44 and 1.06; 95%CI: 0.86-2.42 and 0.67-1.68; p = 0.17 and 0.80) was not prognostic. CT-VPI by an attending radiologist was prognostic only in radiologically solid tumors (HR, 1.82; 95%CI: 1.07-3.07; p = 0.03). CONCLUSION: The diagnostic performance and prognostic value of CT-VPI are limited in clinical stage I lung adenocarcinomas. This feature may be applied for radiologically solid tumors, but substantial reader variability should be overcome. CLINICAL RELEVANCE STATEMENT: Although the diagnostic performance and prognostic value of CT-VPI are limited in clinical stage I lung adenocarcinomas, this parameter may be applied for radiologically solid tumors with appropriate caution regarding inter-reader variability. KEY POINTS: • Use of CT-defined visceral pleural invasion in clinical staging should be cautious, because prognostic value of CT-defined visceral pleural invasion remains unexplored. • Diagnostic performance and prognostic value of CT-defined visceral pleural invasion varied among radiologists and deep learning. • Role of CT-defined visceral pleural invasion in clinical staging may be limited to radiologically solid tumors.

Real-time ultrasound guidance versus fluoroscopic guidance in thoracic epidural catheter placement: a single-center, non-inferiority, randomized, active-controlled trial.

INTRODUCTION: Fluoroscopy can improve the success rate of thoracic epidural catheter placement (TECP). Real-time ultrasound (US)-guided TECP was recently introduced and showed a high first-pass success rate. We tested whether real-time US-guided TECP results in a non-inferior first-pass success rate compared with that of fluoroscopy-guided TECP. METHODS: In this single-center, non-inferiority, randomized trial, the primary outcome was the comparison of the first-pass success rate of TECP between real-time US guidance (US group) and fluoroscopic guidance (fluoroscopy group). Secondary outcomes included time to identifying epidural space, procedure time, total number of needle passes, number of skin punctures, final success, and cross-over success. RESULTS: We randomly assigned 132 patients to the allocated groups. The difference in the first-pass success rate between the groups did not exceed the non-inferiority margin of 15% (US group: 66.7% vs fluoroscopy group: 68.2%; difference -1.5%, 95% exact CI: -14.9% to 11.9%). The difference in the final success rate also did not differ between the groups (98.5% vs 100.0%; difference -1.5%, 95% exact CI: -4.0% to 1.0%). The time to identifying epidural space (45.6 (34-62) vs 59.0 (42-77) s, p=0.004) and procedure time (39.5 (28-78) vs 112.5 (93-166) s, p<0.001) were significantly shorter in the US group. CONCLUSIONS: Real-time US guidance provided a non-inferior success rate and shorter time spent on preparation and procedure compared with fluoroscopic guidance in TECP. TRIAL REGISTRATION NUMBER: KCT0006521.

Pulse versus non-pulse corticosteroid therapy in patients with acute exacerbation of idiopathic pulmonary fibrosis.

BACKGROUND AND OBJECTIVE: Corticosteroids are commonly used for the treatment of acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF); however, the optimal initial dose of corticosteroids remains uncertain due to a lack of sufficient evidence. We evaluated whether the administration of a pulse dose of corticosteroids resulted in improved survival outcomes compared with conventional non-pulse dose of corticosteroids. METHODS: We retrospectively analysed 238 patients with AE-IPF treated with corticosteroids at a tertiary referral hospital between January 2013 and December 2021. Based on whether a pulse dose of corticosteroids (methylprednisolone of ≥250 mg/day or equivalent) was administered within 7 days of hospitalization for AE-IPF, the patients were divided into the pulse and non-pulse regimen groups. The survival outcomes were compared between the two groups using multivariable regression and propensity score-matched analyses. RESULTS: Among the 238 patients, 59 patients received pulse dose of corticosteroids, whereas 179 patients received conventional non-pulse dose of corticosteroids. After adjusting for the confounding factors related to the baseline clinical and radiographic severity, compared with the conventional non-pulse regimen, the pulse regimen of corticosteroids did not reduce the risk of mortality at the 3-month (aHR 0.84, 95% CI 0.45-1.38) or 12-month (aHR 0.96, 95% CI 0.60-1.25) follow-ups. Propensity score-matched analysis revealed similar results. CONCLUSION: The survival outcomes of patients with AE-IPF who received a pulse dose of corticosteroids did not differ from those of patients who received conventional non-pulse dose of corticosteroids. Further prospective studies are required to establish the optimal initial dose of corticosteroids for the treatment of AE-IPF.

Value of CT quantification in progressive fibrosing interstitial lung disease: a deep learning approach.

OBJECTIVES: To evaluate the relationship of changes in the deep learning-based CT quantification of interstitial lung disease (ILD) with changes in forced vital capacity (FVC) and visual assessments of ILD progression, and to investigate their prognostic implications. METHODS: This study included ILD patients with CT scans at intervals of over 2 years between January 2015 and June 2021. Deep learning-based texture analysis software was used to segment ILD findings on CT images (fibrosis: reticular opacity + honeycombing cysts; total ILD extent: ground-glass opacity + fibrosis). Patients were grouped according to the absolute decline of predicted FVC (< 5%, 5-10%, and ≥ 10%) and ILD progression assessed by thoracic radiologists, and their quantification results were compared among these groups. The associations between quantification results and survival were evaluated using multivariable Cox regression analysis. RESULTS: In total, 468 patients (239 men; 64 ± 9.5 years) were included. Fibrosis and total ILD extents more increased in patients with larger FVC decline (p < .001 in both). Patients with ILD progression had higher fibrosis and total ILD extent increases than those without ILD progression (p < .001 in both). Increases in fibrosis and total ILD extent were significant prognostic factors when adjusted for absolute FVC declines of ≥ 5% (hazard ratio [HR] 1.844, p = .01 for fibrosis; HR 2.484, p < .001 for total ILD extent) and ≥ 10% (HR 2.918, p < .001 for fibrosis; HR 3.125, p < .001 for total ILD extent). CONCLUSION: Changes in ILD CT quantification correlated with changes in FVC and visual assessment of ILD progression, and they were independent prognostic factors in ILD patients. CLINICAL RELEVANCE STATEMENT: Quantifying the CT features of interstitial lung disease using deep learning techniques could play a key role in defining and predicting the prognosis of progressive fibrosing interstitial lung disease. KEY POINTS: • Radiologic findings on high-resolution CT are important in diagnosing progressive fibrosing interstitial lung disease. • Deep learning-based quantification results for fibrosis and total interstitial lung disease extents correlated with the decline in forced vital capacity and visual assessments of interstitial lung disease progression, and emerged as independent prognostic factors. • Deep learning-based interstitial lung disease CT quantification can play a key role in diagnosing and prognosticating progressive fibrosing interstitial lung disease.

Price increase negotiations to address drug shortages in South Korea's national health insurance.

South Korea has adopted a unique approach to address drug shortages by increasing reimbursement prices within its National Health Insurance Service. This study aims to analyze the characteristics, increase rates, affecting factors, and budget impacts of products that have increased price through the negotiation system. Between 2007 and 2022, there were price increase negotiations over 244 items. Of these, price increase negotiations were successful for 217 items, resulting in an agreement rate of 89%. The average rate of price increase for the agreed-upon products was 37.8%, and the overall budget increase for drugs with price increases (n = 217) was approximately 24.5%. Budget impact of each variable of the negotiated agreements showed that the number of negotiated agreement items was smaller after 2015 than before 2015, but each total budget impact (initial budget, increased budget, and final budget) and the average budget impact were higher. Although domestic companies accounted for a larger overall budget, the average budget per item was larger for multinational companies. The correlation analysis of the ratio of price increase and budget impact variables showed that the ratio of price increase was positively and significantly correlated with the increased budget, while it was negatively but not significantly correlated with the initial and final budgets. The South Korean model of increasing reimbursement prices in public insurance for drugs at risk of shortages serves as an exemplary case for not only securing patient access but also considering budget management.

Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study.

OBJECTIVES: To develop and validate CT-based deep learning (DL) models that learn morphological and histopathological features for lung adenocarcinoma prognostication, and to compare them with a previously developed DL discrete-time survival model. METHODS: DL models were trained to simultaneously predict five morphological and histopathological features using preoperative chest CT scans from patients with resected lung adenocarcinomas. The DL score was validated in temporal and external test sets, with freedom from recurrence (FFR) and overall survival (OS) as outcomes. Discrimination was evaluated using the time-dependent area under the receiver operating characteristic curve (TD-AUC) and compared with the DL discrete-time survival model. Additionally, we performed multivariable Cox regression analysis. RESULTS: In the temporal test set (640 patients; median age, 64 years), the TD-AUC was 0.79 for 5-year FFR and 0.73 for 5-year OS. In the external test set (846 patients; median age, 65 years), the TD-AUC was 0.71 for 5-year OS, equivalent to the pathologic stage (0.71 vs. 0.71 [p = 0.74]). The prognostic value of the DL score was independent of clinical factors (adjusted per-percentage hazard ratio for FFR (temporal test), 1.02 [95% CI: 1.01-1.03; p < 0.001]; OS (temporal test), 1.01 [95% CI: 1.002-1.02; p = 0.01]; OS (external test), 1.01 [95% CI: 1.005-1.02; p < 0.001]). Our model showed a higher TD-AUC than the DL discrete-time survival model, but without statistical significance (2.5-year OS: 0.73 vs. 0.68; p = 0.13). CONCLUSION: The CT-based prognostic score from collective deep learning of morphological and histopathological features showed potential in predicting survival in lung adenocarcinomas. CLINICAL RELEVANCE STATEMENT: Collective CT-based deep learning of morphological and histopathological features presents potential for enhancing lung adenocarcinoma prognostication and optimizing pre-/postoperative management. KEY POINTS: • A CT-based prognostic model was developed using collective deep learning of morphological and histopathological features from preoperative CT scans of 3181 patients with resected lung adenocarcinoma. • The prognostic performance of the model was comparable-to-higher performance than the pathologic T category or stage. • Our approach yielded a higher discrimination performance than the direct survival prediction model, but without statistical significance (0.73 vs. 0.68; p=0.13).

The salvage role of allogeneic hematopoietic stem-cell transplantation in relapsed/refractory diffuse large B cell lymphoma.

To clarify the role of allogeneic hematopoietic stem-cell transplantation (allo-HSCT) in the chimeric antigen receptor T-cell therapy era, we analyzed the clinical characteristics and outcomes of 52 patients treated with allo-HSCT with relapsed/refractory diffuse large B cell lymphoma. Most enrolled patients had previously undergone intensive treatments, the median number of chemotherapy lines was 4, and the median time from diagnosis to allo-HSCT was 27.1 months. Patients were divided into remission-achieved (n = 30) and active-disease (n = 22) groups before allo-HSCT. Over a median follow-up period of 38.3 months, overall survival (OS) and event-free survival (EFS) rates were 38.4% and 30.6%, respectively. The cumulative incidence of relapse (CIR) and the non-relapsed mortality (NRM) were 36.7% and 32.7%, respectively. OS, EFS, and graft-versus-host disease-free, relapse-free survival (GRFS) outcomes were significantly superior in the remission-achieved group with lower CIR. In a multivariate analysis, a shorter interval from diagnosis to allo-HSCT reflected relatively rapid disease progression and showed significantly poor OS and EFS with higher CIR. Patients with active disease had significantly lower EFS, GRFS, and higher CIR. Previous autologous stem-cell transplantation was associated with better GRFS. Allo-HSCT is an established modality with a prominent group of cured patients and still has a role in the CAR T-cell era, particularly given its acceptable clinical outcomes in young patients with chemo-susceptible disease.

The Performance of a Deep Learning-Based Automatic Measurement Model for Measuring the Cardiothoracic Ratio on Chest Radiographs.

OBJECTIVE: Prior studies on models based on deep learning (DL) and measuring the cardiothoracic ratio (CTR) on chest radiographs have lacked rigorous agreement analyses with radiologists or reader tests. We validated the performance of a commercially available DL-based CTR measurement model with various thoracic pathologies, and performed agreement analyses with thoracic radiologists and reader tests using a probabilistic-based reference. MATERIALS AND METHODS: This study included 160 posteroanterior view chest radiographs (no lung or pleural abnormalities, pneumothorax, pleural effusion, consolidation, and n = 40 in each category) to externally test a DL-based CTR measurement model. To assess the agreement between the model and experts, intraclass or interclass correlation coefficients (ICCs) were compared between the model and two thoracic radiologists. In the reader tests with a probabilistic-based reference standard (Dawid-Skene consensus), we compared diagnostic measures-including sensitivity and negative predictive value (NPV)-for cardiomegaly between the model and five other radiologists using the non-inferiority test. RESULTS: For the 160 chest radiographs, the model measured a median CTR of 0.521 (interquartile range, 0.446-0.59) and a mean CTR of 0.522 ± 0.095. The ICC between the two thoracic radiologists and between the model and two thoracic radiologists was not significantly different (0.972 versus 0.959, p = 0.192), even across various pathologies (all p-values > 0.05). The model showed non-inferior diagnostic performance, including sensitivity (96.3% versus 97.8%) and NPV (95.6% versus 97.4%) (p < 0.001 in both), compared with the radiologists for all 160 chest radiographs. However, it showed inferior sensitivity in chest radiographs with consolidation (95.5% versus 99.9%; p = 0.082) and NPV in chest radiographs with pleural effusion (92.9% versus 94.6%; p = 0.079) and consolidation (94.1% versus 98.7%; p = 0.173). CONCLUSION: While the sensitivity and NPV of this model for diagnosing cardiomegaly in chest radiographs with consolidation or pleural effusion were not as high as those of the radiologists, it demonstrated good agreement with the thoracic radiologists in measuring the CTR across various pathologies.

The Effects of Thermocycling on the Physical Properties and Biocompatibilities of Various CAD/CAM Restorative Materials.

The purpose of this study is to evaluate the changes in physical properties and biocompatibilities caused by thermocycling of CAD/CAM restorative materials (lithium disilicate, zirconia reinforced lithium silicate, polymer-infiltrated ceramic network, resin nanoceramic, highly translucent zirconia). A total of 225 specimens were prepared (12.0 × 10.0 × 1.5 mm) and divided into three groups subjected to water storage at 37 °C for 24 h (control group), 10,000 cycles in distilled water at 5-55 °C (first aged group), and 22,000 cycles in distilled water at 5-55 °C (second aged group) [(n= 15, each]). The nanoindentation hardness and Young's modulus (nanoindenter), surface roughness (atomic force microscopy (AFM)), surface texture (scanning electron microscopy (FE-SEM)), elemental concentration (energy dispersive spectroscopy (EDS)) and contact angle were evaluated. The morphology, proliferation and adhesion of cultured human gingival fibroblasts (HGFs) were analyzed. The data were analyzed using one-way ANOVA and Tukey's test (p < 0.05). The results showed that the nanoindentation hardness and Young's modulus were decreased after thermocycling aging. Cell viability and proliferation of the material decreased with aging except for the highly translucent zirconia. Zirconia-reinforced lithium silicate exhibited significantly lower cell viability compared to other materials. The surface roughnesses of all groups increased with aging. Cell viability and Cell adhesion were influenced by various factors, including the surface chemical composition, hydrophilicity, surface roughness, and topography.

Association Between Fat Depletion and Prognosis of Amyotrophic Lateral Sclerosis: CT-Based Body Composition Analysis.

OBJECTIVE: The purpose of this study was to present the results of our investigation of the prognostic value of adipopenia and sarcopenia in patients with amyotrophic lateral sclerosis (ALS). METHODS: Consecutive patients with ALS with abdominal computed tomography (CT) were retrospectively identified at a single tertiary hospital between January 2010 and July 2021. Deep learning-based volumetric CT body composition analysis software was used to obtain abdominal waist fat volume, fat attenuation, and skeletal muscle area at the L3 level, then normalized to the fat volume index (FVI) and skeletal muscle index (SMI). Adipopenia and sarcopenia were defined as the sex-specific lowest quartile and SMI reference values, respectively. The associations of CT-derived body composition parameters with clinical variables, such as body mass index (BMI) and creatinine, were evaluated by Pearson correlation analyses, and associations with survival were assessed using the multivariable Cox regression analysis. RESULTS: Eighty subjects (40 men, 65.5 ± 9.4 years of age) were investigated (median interval between disease onset and CT examination = 25 months). The mean BMI at the CT examination was 20.3 ± 4.3 kg/m2 . The BMI showed a positive correlation with both FVI (R = 0.70, p < 0.001) and SMI (R = 0.63, p < 0.001), and the serum creatinine level was associated with SMI (R = 0.68, p < 0.001). After adjusting for sex, age, King's stage, BMI, creatinine, progression rate, and sarcopenia, adipopenia was associated with shorter survival (hazard ratio [HR] = 5.94, 95% confidence interval [CI] = 1.01, 35.0, p = 0.049). In a subgroup analysis for subjects with nutritional failure (stage 4a), the HR of adipopenia was 15.1 (95% CI = 2.45, 93.4, p = 0.003). INTERPRETATION: Deep learning-based CT-derived adipopenia in patients with ALS is an independent poor prognostic factor for survival. ANN NEUROL 2023;94:1116-1125.

Effect of Human-AI Interaction on Detection of Malignant Lung Nodules on Chest Radiographs.

Background The factors affecting radiologists' diagnostic determinations in artificial intelligence (AI)-assisted image reading remain underexplored. Purpose To assess how AI diagnostic performance and reader characteristics influence detection of malignant lung nodules during AI-assisted reading of chest radiographs. Materials and Methods This retrospective study consisted of two reading sessions from April 2021 to June 2021. Based on the first session without AI assistance, 30 readers were assigned into two groups with equivalent areas under the free-response receiver operating characteristic curve (AUFROCs). In the second session, each group reinterpreted radiographs assisted by either a high or low accuracy AI model (blinded to the fact that two different AI models were used). Reader performance for detecting lung cancer and reader susceptibility (changing the original reading following the AI suggestion) were compared. A generalized linear mixed model was used to identify the factors influencing AI-assisted detection performance, including readers' attitudes and experiences of AI and Grit score. Results Of the 120 chest radiographs assessed, 60 were obtained in patients with lung cancer (mean age, 67 years ± 12 [SD]; 32 male; 63 cancers) and 60 in controls (mean age, 67 years ± 12; 36 male). Readers included 20 thoracic radiologists (5-18 years of experience) and 10 radiology residents (2-3 years of experience). Use of the high accuracy AI model improved readers' detection performance to a greater extent than use of the low accuracy AI model (area under the receiver operating characteristic curve, 0.77 to 0.82 vs 0.75 to 0.75; AUFROC, 0.71 to 0.79 vs 0.7 to 0.72). Readers who used the high accuracy AI showed a higher susceptibility (67%, 224 of 334 cases) to changing their diagnosis based on the AI suggestions than those using the low accuracy AI (59%, 229 of 386 cases). Accurate readings at the first session, correct AI suggestions, high accuracy Al, and diagnostic difficulty were associated with accurate AI-assisted readings, but readers' characteristics were not. Conclusion An AI model with high diagnostic accuracy led to improved performance of radiologists in detecting lung cancer on chest radiographs and increased radiologists' susceptibility to AI suggestions. © RSNA, 2023 Supplemental material is available for this article.

Specific Signal Transduction of Constitutively Activating (D576G) and Inactivating (R476H) Mutants of Agonist-Stimulated Luteinizing Hormone Receptor in Eel.

We investigated the mechanism of signal transduction using inactivating (R476H) and activating (D576G) mutants of luteinizing hormone receptor (LHR) of eel at the conserved regions of intracellular loops II and III, respectively, naturally occurring in mammalian LHR. The expression of D576G and R476H mutants was approximately 58% and 59%, respectively, on the cell surface compared to those of eel LHR-wild type (wt). In eel LHR-wt, cAMP production increased upon agonist stimulation. Cells expressing eel LHR-D576G, a highly conserved aspartic acid residue, exhibited a 5.8-fold increase in basal cAMP response; however, the maximal cAMP response by high-agonist stimulation was approximately 0.62-fold. Mutation of a highly conserved arginine residue in the second intracellular loop of eel LHR (LHR-R476H) completely impaired the cAMP response. The rate of loss in cell-surface expression of eel LHR-wt and D576G mutant was similar to the agonist recombinant (rec)-eel LH after 30 min. However, the mutants presented rates of loss higher than eel LHR-wt did upon rec-eCG treatment. Therefore, the activating mutant constitutively induced cAMP signaling. The inactivating mutation resulted in the loss of LHR expression on the cell surface and no cAMP signaling. These data provide valuable information regarding the structure-function relationship of LHR-LH complexes.