Prognosis Comparison Between Chronic Hepatitis B Patients Receiving a Finite Course of Tenofovir and Entecavir Treatment: A Nationwide Cohort Study in Taiwan

PurposeEntecavir (ETV) and tenofovir disoproxil fumarate (TDF) are both recommended as first-line treatments for patients with chronic hepatitis B virus (CHB) infection according to international HBV treatment guidelines. However, recent studies reported conflicting results regarding the preferred antiviral in the prevention of hepatocellular carcinoma (HCC). This cohort study aimed to investigate this issue by using Taiwan's National Health Insurance Research Database, wherein a “finite” but not life-long treatment policy was applied.MethodsFrom January 2008 to December 2013, a total of 12,388 consecutive adult patients with CHB who received a finite course of TDF treatment (n = 1250) or ETV treatment (n = 11,138) were analyzed through screening for study eligibility followed by the 1:4 propensity score matching method.FindingsIn the entire cohort, the annual incidence and survival between the ETV and TDF groups were not significantly different regarding HCC occurrence (2.05 vs 2.74 per 100 patient-years [PY]; P = 0.055; hazard ratio [HR], 0.975; log-rank, P = 0.966), cirrhosis-related complications (1.9 vs 2.4 per 100 PY; P = 0.149; HR, 0.869; log-rank, P = 0.388), or all-cause mortality (2.16 vs 1.6 per 100 PY; P = 0.119; HR, 0.831; log-rank, P = 0.342), respectively. Propensity score matching analyses yielded similar results regarding HCC occurrence, cirrhosis-related complications, and all-cause mortality. In addition, these findings were consistently reproduced in the subgroups of patients with chronic hepatitis and cirrhosis that developed before antiviral treatment.ImplicationsETV and TDF did not significantly differ in prevention of HCC occurrence or reduction of cirrhosis-related complications and all-cause mortality in patients with CHB receiving a finite period of treatment.     

Hyperamylasemia grade versus drain fluid amylase: which better predicts pancreatectomy outcomes?

BackgroundThe clinical importance of postoperative hyperamylasemia (POHA) grade is unknown. Our objectives were to evaluate the association of POHA grade with clinically relevant postoperative pancreatic fistula (CR-POPF) and compare its prognostic utility against postoperative day 1 drain fluid amylase (DFA-1).MethodsPatients who underwent pancreatectomy from January 2019 through March 2020 were identified in the ACS NSQIP pancreatectomy-targeted dataset. POHA grade was assigned using post-operative serum amylase and clinical sequelae. The primary outcome was CR-POPF within 30 days. The association of POHA grade with CR-POPF was assessed using multivariable logistic regression, and c-statistics were used to compare POHA grade versus DFA-1.ResultsPOHA occurred in 520 patients at 98 hospitals, including 261 (50.2%) with grade A, 234 (45.0%) with grade B, and 25 (4.8%) with grade C POHA. CR-POPFs were increased among patients with grade B (66.2%, OR 9.28 [5.84–14.73]) and C (68.0%, OR 10.50 [3.77–29.26]) versus grade A POHA (19.2%). POHA-inclusive models better predicted CR-POPF than those with DFA-1 alone (p < 0.002) and models with both predictors outperformed POHA alone (p = 0.039).ConclusionPOHA grade represents a measure of post-pancreatectomy outcomes that predicts CR-POPF and outperforms DFA-1 but must be aligned with new international definitions.     

Skin3D: Detection and longitudinal tracking of pigmented skin lesions in 3D total-body textured meshes

We present an automated approach to detect and longitudinally track skin lesions on 3D total-body skin surface scans. The acquired 3D mesh of the subject is unwrapped to a 2D texture image, where a trained objected detection model, Faster R-CNN, localizes the lesions within the 2D domain. These detected skin lesions are mapped back to the 3D surface of the subject and, for subjects imaged multiple times, we construct a graph-based matching procedure to longitudinally track lesions that considers the anatomical correspondences among pairs of meshes and the geodesic proximity of corresponding lesions and the inter-lesion geodesic distances.We evaluated the proposed approach using 3DBodyTex, a publicly available dataset composed of 3D scans imaging the coloured skin (textured meshes) of 200 human subjects. We manually annotated locations that appeared to the human eye to contain a pigmented skin lesion as well as tracked a subset of lesions occurring on the same subject imaged in different poses. Our results, when compared to three human annotators, suggest that the trained Faster R-CNN detects lesions at a similar performance level as the human annotators. Our lesion tracking algorithm achieves an average matching accuracy of 88% on a set of detected corresponding pairs of prominent lesions of subjects imaged in different poses, and an average longitudinal accuracy of 71% when encompassing additional errors due to lesion detection. As there currently is no other large-scale publicly available dataset of 3D total-body skin lesions, we publicly release over 25,000 3DBodyTex manual annotations, which we hope will further research on total-body skin lesion analysis.     

Prognostic models to predict survival in patients with pancreatic cancer: a systematic review

BackgroundPancreatic ductal adenocarcinoma (PDAC) has poor survival. Current treatments offer little likelihood of cure or long-term survival. This systematic review evaluates prognostic models predicting overall survival in patients diagnosed with PDAC.MethodsWe conducted a comprehensive search of eight electronic databases from their date of inception through to December 2019. Studies that published models predicting survival in patients with PDAC were identified.Results3297 studies were identified; 187 full-text articles were retrieved and 54 studies of 49 unique prognostic models were included. Of these, 28 (57.1%) were conducted in patients with advanced disease, 17 (34.7%) with resectable disease, and four (8.2%) in all patients. 34 (69.4%) models were validated, and 35 (71.4%) reported model discrimination, with only five models reporting values >0.70 in both derivation and validation cohorts. Many (n = 27) had a moderate to high risk of bias and most (n = 33) were developed using retrospective data. No variables were unanimously found to be predictive of survival when included in more than one study.ConclusionMost prognostic models were developed using retrospective data and performed poorly. Future research should validate instruments performing well locally in international cohorts and investigate other potential predictors of survival.     

CT Densitometry and Morphology of Radiofrequency-Ablated Stage IA Non–Small Cell Lung Cancer: Results from the American College of Surgeons Oncology Group Z4033 (Alliance) Trial

PurposeTo evaluate tumor and ablation zone morphology and densitometry related to tumor recurrence in participants with Stage IA non–small cell lung cancer undergoing radiofrequency ablation in a prospective, multicenter trial.Materials and MethodsForty-five participants (median 76 years old; 25 women; 20 men) from 16 sites were followed for 2 years (December 2006 to November 2010) with computed tomography (CT) densitometry. Imaging findings before and after ablation were recorded, including maximum CT attenuation (in Hounsfield units) at precontrast and 45-, 90-, 180-, and 300-s postcontrast.ResultsEvery 1-cm increase in the largest axial diameter of the ablation zone at 3-months’ follow-up compared to the index tumor reduced the odds of 2-year recurrence by 52% (P = .02). A 1-cm difference performed the best (sensitivity, 0.56; specificity, 0.93; positive likelihood ratio of 8). CT densitometry precontrast and at 45 seconds showed significantly different enhancement patterns in a comparison among pretreated lung cancer (delta = +61.2 HU), tumor recurrence (delta = +57 HU), and treated tumor/ablation zone (delta [change in attenuation] = +16.9 HU), (P < .0001). Densitometry from 45 to 300 s was also different among pretreated tumor (delta = −6.8 HU), recurrence (delta = −11.2 HU), and treated tumor (delta = +12.1 HU; P = .01). Untreated and residual tumor demonstrated washout, whereas treated tumor demonstrated increased attenuation.ConclusionsAn ablation zone ≥1 cm larger than the initial tumor, based on 3-month follow-up imaging, is recommended to decrease odds of recurrence. CT densitometry can delineate tumor versus treatment zones.