scholarly journals External Validation of UDCA Response Score in Slovak and Croatian Patients with Primary Biliary Cholangitis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jakub Gazda ◽  
Martin Janicko ◽  
Sylvia Drazilova ◽  
Ivica Grgurevic ◽  
Tajana Filipec Kanizaj ◽  
...  

Background. Ursodeoxycholic acid response score (URS) is a prognostic model that estimates the baseline probability of treatment response after 12 months of ursodeoxycholic acid (UDCA) therapy in patients with primary biliary cholangitis (PBC). Aim. To independently evaluate the predictive performance of the URS model. Methods. We used a cohort of Slovak and Croatian treatment-naïve PBC patients to quantify the discrimination ability using the area under receiver operating characteristic curve (AUROC) and its 95% confidence interval (CI). Furthermore, we evaluated the calibration using calibration belts. The primary outcome was treatment response after 12 months of UDCA therapy defined as values of alkaline phosphatase ≤1.67 × upper limit of normal. Results. One hundred and ninety-four patients were included. Median pretreatment age was 56 years (interquartile range 49–62). Treatment response was achieved in 79.38% of patients. AUROC of the URS was 0.81 (95% CI 0.73–0.88) and the calibration belt revealed that response rates were correctly estimated by predicted probabilities. Conclusion. Our results confirm that the URS can be used in treatment-naïve PBC patients for estimating the treatment response probability after 12 months of UDCA therapy.

2021 ◽  
Vol 11 (6) ◽  
pp. 495
Author(s):  
Jakub Gazda ◽  
Sylvia Drazilova ◽  
Martin Janicko ◽  
Ivica Grgurevic ◽  
Tajana Filipec Kanizaj ◽  
...  

Objective: To identify pretreatment laboratory parameters associated with treatment response and to describe the relationship between treatment response and liver decompensation in patients with primary biliary cholangitis treated with ursodeoxycholic acid. Methods: We defined treatment response as both ALP ≤ 1.67 × ULN and total bilirubin ≤ 2 × ULN. Multiple logistic regression analyses were performed to adjust for confounding effects of sociodemographic variables. Results: Pretreatment total bilirubin ((TB); OR = 0.3388, 95%CI = 0.1671–0.6077), ALT (OR = 0.5306, 95%CI = 0.3830–0.7080), AST (OR = 0.4065, 95%CI = 0.2690–0.5834), ALP (OR = 0.3440, 95%CI = 0.2356–0.4723), total cholesterol ((TC); OR = 0.7730, 95%CI = 0.6242–0.9271), APRI (OR = 0.3375, 95%CI = 0.1833–0.5774), as well as pretreatment albumin (OR = 1.1612, 95%CI = 1.0706–1.2688) and ALT/ALP (OR = 2.4596, 95%CI = 1.2095–5.5472) were associated with treatment response after six months of treatment. Pretreatment TB (OR = 0.2777, 95%CI = 0.1288–0.5228), ALT (OR = 0.5968, 95%CI = 0.4354–0.7963), AST (OR = 0.4161, 95%CI = 0.2736–0.6076), ALP (OR = 0.4676, 95%CI = 0.3487–0.6048), APRI (OR = 0.2838, 95%CI = 0.1433–0.5141), as well as pretreatment albumin (OR = 1.2359, 95%CI = 1.1257–1.3714) and platelet count (OR = 1.0056, 95%CI = 1.0011–1.0103) were associated with treatment response after 12 months of treatment. Treatment response after 6 months of UDCA therapy is significantly associated with treatment response after 12 months of UDCA therapy (OR = 25.2976, 95% CI = 10.5881–68.4917). Treatment responses after 6 and 12 months of UDCA therapy decrease the risk of an episode of liver decompensation in PBC patients (OR = 12.1156, 95%CI = 3.7192–54.4826 and OR = 21.6000, 95%CI = 6.6319–97.3840, respectively). Conclusions: There are several pretreatment laboratory parameters associated with treatment response in patients with primary biliary cholangitis. Treatment response after six months is significantly associated with treatment response after 12 months of ursodeoxycholic acid (UDCA) therapy. Treatment responses after 6 and 12 months of UDCA decrease the risk of an episode of liver decompensation.


2019 ◽  
Vol 6 (1) ◽  
pp. e000298 ◽  
Author(s):  
Thitima Benjachat Suttichet ◽  
Wonngarm Kittanamongkolchai ◽  
Chutipha Phromjeen ◽  
Sirirat Anutrakulchai ◽  
Thanachai Panaput ◽  
...  

BackgroundTNF-like weak inducer of apoptosis (TWEAK) is a proinflammatory molecule that plays a key role in active inflammation of lupus nephritis (LN). Urine TWEAK (uTWEAK) levels were found to be associated with renal disease activity among patients with LN. Here, we determined whether serial measurements of uTWEAK during induction therapy could predict treatment response or not.MethodsSpot urine samples were collected from patients with biopsy-proven active LN at time of flare, and 3 and 6 months after flare to assess the uTWEAK levels. All patients received standard immunosuppressive therapy and treatment response was evaluated at 6 months. The performance of uTWEAK as a predictor for treatment response was compared with clinically used biomarkers for patients with LN.ResultsAmong 110 patients with LN, there were 29% complete responders (CR), 34% partial responders (PR) and 37% non-responders (NR). On average, uTWEAK level was consistently low in CR, trended down by 3 months in PR and persistently elevated in NR. uTWEAK levels at month 3 were able to predict complete response at month 6 (OR adjusted for age, sex and creatinine=0.34 [95% CI 0.15 to 0.80], the area under the receiver operating characteristic curve [ROC-AUC]=0.68, p=0.02). The optimal threshold for uTWEAK level at month 3 was 0.46 pg/mgCr, discriminating complete response with 70% sensitivity and 63% specificity. Combining uTWEAK and urine protein at month 3 improved predictive performance for complete response at 6 months (ROC-AUC 0.83, p<0.001).ConclusionsIn addition to urine protein, uTWEAK level at 3 months after flare can improve the accuracy in predicting complete response at 6 months of induction therapy.


2021 ◽  
Vol 000 (000) ◽  
pp. 000-000
Author(s):  
Yanyun Shu ◽  
Yuhu Song ◽  
Tao Bai ◽  
Xiaoli Pan ◽  
Haitao Shang ◽  
...  

2020 ◽  
Vol 38 (24) ◽  
pp. 2719-2727 ◽  
Author(s):  
Serigne N. Lo ◽  
Jiawen Ma ◽  
Richard A. Scolyer ◽  
Lauren E. Haydu ◽  
Jonathan R. Stretch ◽  
...  

PURPOSE For patients with primary cutaneous melanoma, the risk of sentinel node (SN) metastasis varies according to several clinicopathologic parameters. Patient selection for SN biopsy can be assisted by National Comprehensive Cancer Network (NCCN) and ASCO/Society of Surgical Oncology (SSO) guidelines and the Memorial Sloan Kettering Cancer Center (MSKCC) online nomogram. We sought to develop an improved online risk calculator using alternative clinicopathologic parameters to more accurately predict SN positivity. PATIENTS AND METHODS Data from 3,477 patients with melanoma who underwent SN biopsy at Melanoma Institute Australia (MIA) were analyzed. A new nomogram was developed by replacing body site and Clark level from the MSKCC model with mitotic rate, melanoma subtype, and lymphovascular invasion. The predictive performance of the new nomogram was externally validated using data from The University of Texas MD Anderson Cancer Center (n = 3,496). RESULTS The MSKCC model receiver operating characteristic curve had a predictive accuracy of 67.7% (95% CI, 65.3% to 70.0%). The MIA model had a predictive accuracy of 73.9% (95% CI, 71.9% to 75.9%), a 9.2% increase in accuracy over the MSKCC model ( P < .001). Among the 2,748 SN-negative patients, SN biopsy would not have been offered to 22.1%, 13.4%, and 12.4% based on the MIA model, the MSKCC model, and NCCN or ASCO/SSO criteria, respectively. External validation generated a C-statistic of 75.0% (95% CI, 73.2% to 76.7%). CONCLUSION A robust nomogram was developed that more accurately estimates the risk of SN positivity in patients with melanoma than currently available methods. The model only requires the input of 6 widely available clinicopathologic parameters. Importantly, the number of patients undergoing unnecessary SN biopsy would be significantly reduced compared with use of the MSKCC nomogram or the NCCN or ASCO/SSO guidelines, without losing sensitivity. An online calculator is available at www.melanomarisk.org.au .


2020 ◽  
Vol 40 (8) ◽  
pp. 1926-1933 ◽  
Author(s):  
Minami Yagi ◽  
Kosuke Matsumoto ◽  
Atsumasa Komori ◽  
Masanori Abe ◽  
Naoaki Hashimoto ◽  
...  

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Nauman Jahangir ◽  
Nicholas Lanzotti ◽  
Kyle Gollon ◽  
Mehwish Farooqi ◽  
Michael Buhnerkempe ◽  
...  

Introduction: In recent years, many scoring models have been proposed to predict clinical outcomes after acute ischemic stroke. Aim of our study was to perform a comparative analysis of these scoring systems to assess predictive reliability. Method: This retrospective single center study included 166 community-based patients presenting with an acute ischemic stroke between 2015 and 2018 who had undergone mechanical thrombectomy with or without IV r-tPA administration prior to the procedure. Patients with unknown 90 day Modified Ranking Scale (mRS) were excluded from the study. We included SPAN-100, THRIVE, HIAT2, iScore , TPI, DRAGON, ASTRAL and HAT predictive models to our study. To predict MRS at 90 days, we first dichotomize mRS into two groups: scores of 0 and 1 and scores 2 and above. We then used logistic regression to find the association between a stroke score and the probability of having a 90-day mRS of 2 or above. Separate univariate logistic regressions were fit for each stroke score. We assessed the ability of each stroke score to predict 90-day mRS using the area-under-the-curve (AUC) of the receiver operating characteristic curve (ROC - plot of sensitivity against 1-specificity). AUC values range from 0.5 to 1 with values above 0.7 showing good discriminatory ability. Results: SPAN-100, HIAT2, iScore, and ASTRAL scores have similar predictive ability with AUC values over 0.7 (Table 1). The ASTRAL score had the highest predictive ability with a score above 31.5 indicating a high likelihood of a 90-day MRS ≥ 2 (Table 1). The TPI, DRAGON, and HAT scores all had AUCs below 0.65 indicating poor predictive performance in our data. Conclusion: The SPAN-100, HIAT2, iScore, and ASTRAL scores reliably predicts 90-day mRS of 2 or greater in patients with acute ischemic stroke.


Author(s):  
Jian Zhang ◽  
Linhai Xiao ◽  
Shengyu Pu ◽  
Yang Liu ◽  
Jianjun He ◽  
...  

Abstract Background Pathological responses of neoadjuvant chemotherapy (NCT) are associated with survival outcomes in patients with breast cancer. Previous studies constructed models using out-of-date variables to predict pathological outcomes, and lacked external validation, making them unsuitable to guide current clinical practice. Objective The aim of this study was to develop and validate a nomogram to predict the objective remission rate (ORR) of NCT based on pretreatment clinicopathological variables. Methods Data from 110 patients with breast cancer who received NCT were used to establish and calibrate a nomogram for pathological outcomes based on multivariate logistic regression. The predictive performance of this model was further validated using a second cohort of 55 patients with breast cancer. Discrimination of the prediction model was assessed using an area under the receiver operating characteristic curve (AUC), and calibration was assessed using calibration plots. The diagnostic odds ratio (DOR) was calculated to further evaluate the performance of the nomogram and determine the optimal cut-off value. Results The final multivariate regression model included age, NCT cycles, estrogen receptor, human epidermal growth factor receptor 2 (HER2), and lymphovascular invasion. A nomogram was developed as a graphical representation of the model and showed good calibration and discrimination in both sets (an AUC of 0.864 and 0.750 for the training and validation cohorts, respectively). Finally, according to the Youden index and DORs, we assigned an optimal ORR cut-off value of 0.646. Conclusion We developed a nomogram to predict the ORR of NCT in patients with breast cancer. Using the nomogram, for patients who are operable and whose ORR is < 0.646, we believe that the benefits of NCT are limited and these patients can be treated directly using surgery.


2018 ◽  
Vol 2 (6) ◽  
pp. 676-682 ◽  
Author(s):  
Angela C. Cheung ◽  
Aliya F. Gulamhusein ◽  
Brian D. Juran ◽  
Erik M. Schlicht ◽  
Bryan M. McCauley ◽  
...  

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