Physicians In Clinical Decision Research Articles

Development of a nomogram to predict the probability of survival in hypopharyngeal squamous cell cancer based on systemic inflammation and nutritional indicators

The prognostic significance of various systemic inflammatory and nutritional markers in hypopharyngeal squamous cell carcinoma (HPSCC) remains unclear. This study aimed to develop a nomogram to predict survival probabilities in patients undergoing HPSCC resection surgery based on these markers, which could help in the treatment of HPSCC. The study included data from 236 HPSCC patients. The most predictive systemic inflammatory and nutritional markers were identified through the area under the prognostic curve (AUC). Using COX regression analysis, independent risk factors were pinpointed and used to create and validate a predictive nomogram. The cut-off values of systemic immune-inflammatory index (SII) and advanced lung cancer inflammatory index (ALI) were 27.80 and 791.35, respectively. The constructed nomogram incorporated tumor stage, age, ALI, and SII. The AUC values for 1-year, 3-year, and 5-year survival prediction were 0.820, 0.721, and 0.723, respectively. Calibration and decision curves demonstrated the substantial clinical utility of the model. SII and ALI possess significant prognostic importance in HPSCC. The developed nomogram, which includes these markers, offers a practical tool for estimating patient survival probabilities, aiding physicians in clinical decision-making for high-risk patients.

Multinational Drug Survival Study of Omalizumab in Patients With Chronic Urticaria and Potential Predictors for Discontinuation

Treating patients with chronic urticaria using omalizumab has been shown to be safe and effective in randomized clinical trials. Multinational studies on long-term omalizumab performance in chronic urticaria in clinical practice settings are lacking, especially on drug survival. Drug survival, which refers to the length of time that patients are treated with a specific drug, is a comprehensive outcome covering effectiveness, safety, and patient and physician preferences. Furthermore, little is known about the reasons and potential predictors for omalizumab discontinuation. To investigate omalizumab drug survival as well as reasons and potential predictors for discontinuation in a large, diverse population. This international multicenter cohort study was conducted at 14 Urticaria Centers of Reference and Excellence in 10 countries, including all patients with chronic urticaria from these centers who were ever treated with omalizumab. Drug survival analysis was performed to assess time to discontinuation. Patient characteristics and treatment protocols were investigated by Cox regression analysis to identify potential predictors for omalizumab discontinuation. In 2325 patients with chronic urticaria who started omalizumab between June 2009 and July 2022, the mean (SD) age of the cohort was 42 (6) years, and 1650 participants (71%) were female. Overall omalizumab survival rates decreased from 76% to 39% after 1 to 7 years, respectively (median survival time, 3.3 [95 % CI, 2.9-4.0] years), primarily due to discontinuation from well-controlled disease in 576 patients (65%). Ineffectiveness and adverse effects were reasons for discontinuation in a far smaller proportion of patients, totaling 164 patients (18%) and 31 patients (4%), respectively. Fast treatment response was associated with higher rates of omalizumab discontinuation due to well-controlled disease (hazard ratio, 1.45 [95% CI, 1.20-1.75]), and disease duration of more than 2 years was associated with lower rates of discontinuation due to well-controlled disease (HR, 0.81 [95% CI, 0.67-0.98]). Immunosuppressive cotreatment at the start of omalizumab and autoimmune disease was associated with a higher risk for discontinuation due to ineffectiveness (HR, 1.65 [95% CI, 1.12-2.42]). The presence of spontaneous wheals (HR, 0.62 [95% CI, 0.41-0.93]) and access to higher dosages (HR, 0.40 [95% CI, 0.27-0.58) were both associated with a lower risk for discontinuation of omalizumab due to ineffectiveness. This multinational omalizumab drug survival cohort study demonstrated that treatment of chronic urticaria with omalizumab in a clinical setting is effective and safe, and well-controlled disease is the main reason for treatment discontinuation. These findings on omalizumab drug survival rates and reasons and potential predictors for discontinuation may guide patients and physicians in clinical decision-making and expectation management. These results may call for the identification of biomarkers for chronic urticaria remission in complete responders to omalizumab treatment.

Real-world unified airway benefits of mepolizumab: Effectiveness in patients with asthma and comorbid nasal polyps

BackgroundNasal polyps (NPs) are commonly associated with chronic rhinosinusitis (CRS). In keeping with the unified airway hypothesis, asthma and CRS with NP (CRSwNP) frequently co-occur, share a similar pathophysiology, and are often treated with oral corticosteroids (OCS); however, a need for alternative treatment options for patients with comorbid asthma and CRSwNP remains. ObjectiveTo characterize the short- and long-term dual airway effectiveness of the anti–interleukin-5 monoclonal antibody, mepolizumab, in real-world patients with asthma and comorbid NP. MethodsAdult patients with CRSwNP who initiated mepolizumab from November 1, 2014, to September 30, 2021, were identified from 2 Merative MarketScan Research Databases. Outcomes were compared for the 12 months pre- and post-mepolizumab initiation and a variable follow-up period. Primary outcomes included the following: annual rate and proportion of patients with NP- and asthma-related exacerbations; NP surgery occurrences; all-cause OCS claims, number of OCS bursts, and daily OCS dose; all-cause and NP-related health care resource utilization. ResultsDuring the 12 months post-index, patients experienced fewer NP- and asthma-related exacerbations, required fewer sinus surgeries, and reduced use of OCS, with fewer all-cause OCS claims and OCS bursts. Significant reductions in asthma exacerbation-related and NP-related health care resource utilization were also observed. ConclusionThis study illustrated the near- and long-term real-world effectiveness of mepolizumab treatment, with a focus on dual lower and upper airway benefit from single-agent add-on therapy. These results may aid physicians in clinical decision-making for patients with asthma and comorbid CRSwNP with complex care needs.

Efficacy of encorafenib/binimetinib in patients with metastatic melanoma with brain metastases: Results from the nationwide Dutch Melanoma Treatment Registry.

9528 Background: Data on the effectiveness of encorafenib plus binimetinib in patients with melanoma brain metastases (BMs) are lacking. Therefore, we aimed to investigate the effectiveness of encorafenib/binimetinib treatment in melanoma patients with BMs. Methods: All melanoma patients with BMs treated with encorafenib/binimetinib between 2019 and 2023 in the Netherlands were included from the nationwide Dutch Melanoma Treatment Registry. Patients with prior BRAF/MEK inhibition treatment were excluded. We analyzed overall response rates (ORR), progression-free (PFS), and overall survival (OS) from start of encorafenib/binimetinib. We performed subgroup analysis for symptomatic versus asymptomatic BMs and previous treatment versus no previous treatment. Results: In total, 208 patients were included. Median age was 61 years and 58.2% of the patients was male. Lactate dehydrogenase levels were elevated in 48.1% of the patients and symptomatic BMs were present in 63.5%. Of all patients, 41.8% received prior immunotherapy and for 58.2% encorafenib/binimetinib was the first-line treatment. The median follow-up duration was 23.2 months. The ORR was 67.3%. Median PFS was 5.6 months (95% confidence interval (CI): 4.9-6.2) and median OS was 10.9 months (95% CI: 9.6-14.0). OS was significantly shorter in patients with symptomatic BMs versus asymptomatic BMs (median 9.7 versus 22.9 months, p<0.01), while PFS was similar (median 5.6 versus 5.8 months, p=0.07). Previously untreated patients had worse prognostic characteristics than previously treated patients. PFS was not significantly different between patients with versus without previous systemic treatment (median 8.8 versus 5.2 months, p=0.08), while OS from start of encorafenib/binimetinib was longer for previously treated patients (median 15.9 versus 9.6 months, p<0.01). Conclusions: Encorafenib plus binimetinib has clinical activity in real world melanoma patients with BMs, but PFS and OS are shorter than previously reported for patients without brain metastases. These data may aid physicians in clinical decision-making.

MRI-based Deep Learning Models for Preoperative Breast Volume and Density Assessment Assisting Breast Reconstruction.

The volume of the implant is the most critical element of breast reconstruction, so it is necessary to accurately assess the preoperative volume of the healthy and affected breasts and select the appropriate implant for placement. Accurate and automated methods for quantitative assessment of breast volume can optimize breast reconstruction surgery and assist physicians in clinical decision making. The aim of this study was to develop an artificial intelligence model for automated segmentation of the breast and measurement of volume. A total of 249 subjects undergoing breast reconstruction surgery were enrolled in this study. Subjects underwent preoperative breast MRI, and the breast region manually outlined by the imaging physician served as the gold standard for volume measurement by the automated segmentation model. In this study, we developed three automated algorithms for automatic segmentation of breast regions, including a simple alignment model, an alignment dynamic encoding model, and a deep learning model. The volumetric agreement between the three automated segmentation algorithms and the breast regions manually segmented by imaging physicians was evaluated by calculating the mean square error (MSE) and intragroup correlation coefficient (ICC), and the reproducibility of the automated segmentation of the breast regions was assessed by the test-retest step. The three breast automated segmentation models developed in this study (simple registration model, dynamic programming model, and deep learning model) showed strong ICC with manual segmentation of the breast region, with MSEs of 1.124, 0.693, and 0.781, and ICCs of 0.975 (95% CI, 0.869-0.991), 0.986 (95% CI, 0.967-0.996), and 0.983 (95% CI, 0.961-0.992), respectively. Regarding the test-retest results of breast volume, the dynamic programming model performed the best with an MSE of 0.370 and an ICC of 0.993 (95% CI, 0.982-0.997), followed by the deep learning algorithm with an MSE of 0.741 and an ICC of 0.983 (95% CI, 0.956-0.993), and the simple registration algorithm with an MSE of 0.763 and an ICC of 0.982 (95% CI, 0.949-0.993). The reproducibility of the breast region segmented by the three automated algorithms was higher than that of manual segmentation by different radiologists. The three automated breast segmentation algorithms developed in this study generate accurate and reliable breast regions, enable highly reproducible breast region segmentation and automated volume measurements, and provide a valuable tool for surgical selection of appropriate prostheses. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Performance of a Large Language Model in the Generation of Clinical Guidelines for Antibiotic Prophylaxis in Spine Surgery.

Large language models, such as chat generative pre-trained transformer (ChatGPT), have great potential for streamlining medical processes and assisting physicians in clinical decision-making. This study aimed to assess the potential of ChatGPT's 2 models (GPT-3.5 and GPT-4.0) to support clinical decision-making by comparing its responses for antibiotic prophylaxis in spine surgery to accepted clinical guidelines. ChatGPT models were prompted with questions from the North American Spine Society (NASS) Evidence-based Clinical Guidelines for Multidisciplinary Spine Care for Antibiotic Prophylaxis in Spine Surgery (2013). Its responses were then compared and assessed for accuracy. Of the 16 NASS guideline questions concerning antibiotic prophylaxis, 10 responses (62.5%) were accurate in ChatGPT's GPT-3.5 model and 13 (81%) were accurate in GPT-4.0. Twenty-five percent of GPT-3.5 answers were deemed as overly confident while 62.5% of GPT-4.0 answers directly used the NASS guideline as evidence for its response. ChatGPT demonstrated an impressive ability to accurately answer clinical questions. GPT-3.5 model's performance was limited by its tendency to give overly confident responses and its inability to identify the most significant elements in its responses. GPT-4.0 model's responses had higher accuracy and cited the NASS guideline as direct evidence many times. While GPT-4.0 is still far from perfect, it has shown an exceptional ability to extract the most relevant research available compared to GPT-3.5. Thus, while ChatGPT has shown far-reaching potential, scrutiny should still be exercised regarding its clinical use at this time.

Endovascular Repair of Juxtarenal and Pararenal Abdominal Aortic Aneurysms Using a Novel Low-Profile Fenestrated Custom-Made Endograft: Technical Details and Short-Term Outcomes.

The aim of this study is to share preliminary experiences and outcomes with a novel custom-made fenestrated TREO® Abdominal Stent-Graft System to treat juxtarenal and pararenal abdominal aortic aneurysms (AAAs). Juxtarenal and pararenal AAA patients treated with the custom-made fenestrated TREO® Abdominal Stent-Graft System were included from 4 high-volume European academic medical centers from June 2021 to September 2023. Technical success and 30-day/in-hospital mortality and complications were analyzed. Technical success was defined as successful endovascular implantation of the stent graft with preservation of antegrade flow to the target vessels, and absence of type 1 or 2 endoleak (EL) at the first postoperative computed tomography angiography (CTA). Forty-two consecutive patients were included. The majority of the devices were constructed with 2 (N=4; 9.5%), 3 (N=9; 21.4%), or 4 (N=27; 64%) fenestrations. In 1 case, the device was constructed with a single fenestration (2.4%) and 1 device contained 5 fenestrations (2.4%); 17% had previous AAA repair. Target vessel cannulation with placement of a bridging stent was successful in all but 1 vessel (99, 3%). One aneurysm-related death occurred in the direct postoperative period and 2 limb occlusions necessitated reintervention during admission. In the median follow-up period of 101 (2-620) days, 3 more patients died due to non-aneurysm-related causes. Technical success was achieved in 90% of the cases. Nineteen ELs were seen on the first postoperative CT scan: 1 type 1b EL (N=1; 2%), 15 type 2 ELs (N=15; 36%), and 3 type 3 ELs (N=3%). Eleven patients received more than 1 CT scan during a median follow-up of 361 days (82-620): 3 type 2 ELs resolved and 1 type 3 EL was treated in this period. In the follow-up, 1 patient had a coagulation disorder that caused occlusions of the branches. The results of the first experiences using the custom-made fenestrated TREO® Abdominal Stent-Graft System in Europe are promising. There was a low short-term mortality and morbidity rate in these patients of which 17% had previous AAA repair. Mid-term and long-term follow-up data are needed to evaluate endograft durability and performance. This study shows the first experiences and short-term results of a novel low-profile custom-made device: the custom-made fenestrated TREO® Abdominal Stent-Graft System. Showing these results and experiences can help the physicians in clinical decision-making for their patients.

Medico-legal issues related to emergency physicians' documentation in Canadian emergency departments.

Physician documentation plays a central role in the delivery of safe patient care. It describes a physician's clinical decision-making and supports essential communication between healthcare providers within the patient's circle of care. Good documentation can potentially also decrease a physician's medico-legal risk. This study provides examples of documentation issues attributed to physicians practicing emergency medicine as identified by peer experts in civil legal actions, regulatory authority complaints (College) and hospital complaints (collectively, medico-legal cases) in Canada. We conducted a descriptive study and content analysis of medico-legal cases involving emergency department physicians from a national repository at the Canadian Medical Protective Association. Cases with peer expert criticism of an emergency physician's documentation, which were closed between 2016 and 2020, and occurred in an emergency department were included in our analysis. Of the 1628 cases involving emergency medicine, our inclusion criteria identified that absent or insufficiently detailed documentation was present in 24% of cases (391/1,628). A detailed review of 20% of the cases (79/391), selected randomly, found that documentation issues were most often associated with the assessment and investigation stage of care. This pertained to documenting details of the clinical examination, relevant medical history, diagnosis, and differential diagnosis. For physicians practicing emergency medicine, criticism of documentation was frequently observed in medico-legal cases. Based on the findings of this study and the expert criticism related to documentation, emergency medicine physicians may consider reflecting upon their documentation of the care provided to determine if their documentation provides a clear and accurate chronicle of the care and the rationale for their clinical decisions.

The Underlying Changes in Serum Metabolic Profiles and Efficacy Prediction in Patients with Extensive Ulcerative Colitis Undergoing Fecal Microbiota Transplantation.

(1) Background: Fecal microbiota transplantation (FMT) is an effective treatment for ulcerative colitis (UC). Metabolomic techniques would assist physicians in clinical decision-making. (2) Methods: Patients with active UC undergoing FMT were enrolled in the study and monitored for 3 months. We explored short-term changes in the serum metabolic signatures of groups and the association between baseline serum metabolomic profiles and patient outcomes. (3) Results: Forty-four eligible patients were included in the analysis. Of them, 50.0% and 29.5% achieved clinical response and clinical remission, respectively, 3 months post-FMT. The top two significantly altered pathways in the response group were vitamin B6 metabolism and aminoacyl-tRNA biosynthesis. Both the remission and response groups exhibited an altered and enriched pathway for the biosynthesis of primary bile acid. We found a clear separation between the remission and non-remission groups at baseline, characterized by the higher levels of glycerophosphocholines, glycerophospholipids, and glycerophosphoethanolamines in the remission group. A random forest (RF) classifier was constructed with 20 metabolic markers selected by the Boruta method to predict clinical remission 3 months post-FMT, with an area under the curve of 0.963. (4) Conclusions: FMT effectively induced a response in patients with active UC, with metabolites partially improving post-FMT in the responsive group. A promising role of serum metabolites in the non-invasive prediction of FMT efficacy for UC demonstrated the value of metabolome-informed FMT in managing UC.

Preoperative Frailty Assessment Predicts Postoperative Mortality, Delirium and Pneumonia in Elderly Lung Cancer Patients: A Retrospective Cohort Study.

The purpose of this study was to investigate the predictive value of the 5-factor modified frailty index (mFI-5) for postoperative mortality, delirium and pneumonia in patients over 65 years of age undergoing elective lung cancer surgery. Data were collected from a single-center retrospective cohort study conducted in a general tertiary hospital from January 2017 to August 2019. In total, the study included 1372 elderly patients aged over 65 who underwent elective lung cancer surgery. They were divided into frail group (mFI-5, 2-5), prefrail group (mFI-5, 1) and robust group (mFI-5, 0) on the basis of mFI-5 classification. The primary outcome was postoperative 1-year all-cause mortality. Secondary outcomes were postoperative pneumonia and postoperative delirium. Frailty group had the highest incidence of postoperative delirium (frailty 31.2% versus prefrailty 1.6% versus robust 1.5%, p < 0.001), postoperative pneumonia (frailty 23.5% versus prefrailty 7.2% versus robust 7.7%, p < 0.001), and postoperative 1-year mortality (frailty 7.0% versus prefrailty 2.2% versus robust 1.9%. p < 0.001). Frail patients have significantly longer length of hospitalization than those in the robust group and prefrail patients (p < 0.001). Multivariate analysis showed a clear link between frailty and increased risk of postoperative delirium (aOR 2.775, 95% CI 1.776-5.417, p < 0.001), postoperative pneumonia (aOR 3.291, 95% CI 2.169-4.993, p < 0.001) and postoperative 1-year mortality (aOR 3.364, 95% CI, 1.516-7.464, p = 0.003). mFI-5 has potential clinical utility in predicting postoperative death, delirium and pneumonia incidence in elderly patients undergoing radical lung cancer surgery. Frailty screening of patients (mFI-5) may provide benefits in risk stratification, targeted intervention efforts, and assist physicians in clinical decision-making.

Deep radiomic model based on the sphere–shell partition for predicting treatment response to chemotherapy in lung cancer

BackgroundThe prognosis of chemotherapy is important in clinical decision-making for non-small cell lung cancer (NSCLC) patients. ObjectivesTo develop a model for predicting treatment response to chemotherapy in NSCLC patients from pre-chemotherapy CT images. Materials and MethodsThis retrospective multicenter study enrolled 485 patients with NSCLC who received chemotherapy alone as a first-line treatment. Two integrated models were developed using radiomic and deep-learning-based features. First, we partitioned pre-chemotherapy CT images into spheres and shells with different radii around the tumor (0–3, 3–6, 6–9, 9–12, 12–15 mm) containing intratumoral and peritumoral regions. Second, we extracted radiomic and deep-learning-based features from each partition. Third, using radiomic features, five sphere–shell models, one feature fusion model, and one image fusion model were developed. Finally, the model with the best performance was validated in two cohorts. ResultsAmong the five partitions, the model of 9–12 mm achieved the highest area under the curve (AUC) of 0.87 (95% confidence interval: 0.77–0.94). The AUC was 0.94 (0.85–0.98) for the feature fusion model and 0.91 (0.82–0.97) for the image fusion model. For the model integrating radiomic and deep-learning-based features, the AUC was 0.96 (0.88–0.99) for the feature fusion method and 0.94 (0.85–0.98) for the image fusion method. The best-performing model had an AUC of 0.91 (0.81–0.97) and 0.89 (0.79–0.93) in two validation sets, respectively. ConclusionsThis integrated model can predict the response to chemotherapy in NSCLC patients and assist physicians in clinical decision-making.

Impact of a medical supply bulk-buy program on treatment of patients with coronary artery disease in China: A single-center study.

The Chinese government recently introduced a program to buy medical supplies in bulk to reduce the patient cost burden. For patients undergoing percutaneous coronary intervention (PCI), little is known about the effect on outcomes of this bulk-buy program. This study investigated whether the bulk-buy program to decrease the price of stents used in PCI affected clinical decision-making and outcomes. This single-center study enrolled patients undergoing PCI from January 2020-December 2021. Prices decreased for stents on January 1, 2021, and balloons on March 1, 2021. Patients were grouped by surgical year as either before (2020) or after (2021) policy implementation. All clinical data were collected. To examine whether clinical decision-making for PCI was affected by the bulk-buy program, procedure appropriateness was analyzed using the 2017 appropriate use criteria (AUC). To assess outcomes, the rates of major adverse cardiac and cerebrovascular events (MACCE) and complications were compared between groups. Study participants were 601 patients in 2020 (before bulk buying) and 699 patients in 2021 (after bulk buying). Results of analysis by AUC for procedure appropriateness were 74.5% appropriate, 21.6% may be appropriate, and 3.8% rarely appropriate in 2020, with no differences for patients who underwent PCI in 2021. Between-group comparisons showed MACCE rates of 0.5% in 2020 and 0.6% in 2021, whereas complication rates were 5.5% and 5.7%, respectively. No statistically significant differences were found between groups (p > 0.05). The bulk-buy program did not impact physician clinical decision-making or surgical outcomes for patients undergoing PCI.

Ant Colony Optimization–Rain Optimization Algorithm Based on Hybrid Deep Learning for Diagnosis of Lung Involvement in Coronavirus Patients

With today's rapid increase in population, automatic diagnosis of disease has emerged as a critical subject in the field of medicine. An automatic disease detection framework gives correct, accurate, and rapid outputs, supporting clinicians in making accurate diagnoses while also reducing the number of deaths from disease. This paper aims to develop a system for detecting anomalies, and to reach this objective, various concepts of machine learning, for example, support vector machines, are employed for the construction of a detection system with a deep learning algorithm, termed long short-term memory. Accordingly, the study proposes an approach for detecting lung involvement. A dataset consisting of 4575 CT scan pictures, of which 1525 were from the COVID-19 virus, was employed in the current investigation. The proposed system attained 99.9487% accuracy, 99.9485% specificity, 99.9485% sensitivity, and a 99.8787% F1-score based on experimental results. Based on the data provided, the system was able to accomplish the expected results. The experimental findings highlight the favorable features in improving classification accuracy and selecting the best attributes. The method thus shows promise as a convenient diagnostic tool to aid physicians in clinical decision-making.

Clinical prediction models for serious infections in children: external validation in ambulatory care

BackgroundEarly distinction between mild and serious infections (SI) is challenging in children in ambulatory care. Clinical prediction models (CPMs), developed to aid physicians in clinical decision-making, require broad external validation before clinical use. We aimed to externally validate four CPMs, developed in emergency departments, in ambulatory care.MethodsWe applied the CPMs in a prospective cohort of acutely ill children presenting to general practices, outpatient paediatric practices or emergency departments in Flanders, Belgium. For two multinomial regression models, Feverkidstool and Craig model, discriminative ability and calibration were assessed, and a model update was performed by re-estimation of coefficients with correction for overfitting. For two risk scores, the SBI score and PAWS, the diagnostic test accuracy was assessed.ResultsA total of 8211 children were included, comprising 498 SI and 276 serious bacterial infections (SBI). Feverkidstool had a C-statistic of 0.80 (95% confidence interval 0.77–0.84) with good calibration for pneumonia and 0.74 (0.70–0.79) with poor calibration for other SBI. The Craig model had a C-statistic of 0.80 (0.77–0.83) for pneumonia, 0.75 (0.70–0.80) for complicated urinary tract infections and 0.63 (0.39–0.88) for bacteraemia, with poor calibration. The model update resulted in improved C-statistics for all outcomes and good overall calibration for Feverkidstool and the Craig model. SBI score and PAWS performed extremely weak with sensitivities of 0.12 (0.09–0.15) and 0.32 (0.28–0.37).ConclusionsFeverkidstool and the Craig model show good discriminative ability for predicting SBI and a potential for early recognition of SBI, confirming good external validity in a low prevalence setting of SBI. The SBI score and PAWS showed poor diagnostic performance.Trial registrationClinicalTrials.gov, NCT02024282. Registered on 31 December 2013.

Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor.

Malignant myofibroblastic tumors are a rare group of soft tissue sarcomas, for which a prognosis prediction model is lacking. Based on the Surveillance, Epidemiology, and End Results (SEER) database and cases from Nanjing Drum Tower Hospital, the current study constructed and validated a nomogram to assess overall survival of patients with malignant myofibroblastic tumors. Data of patients with myofibroblastic tumors diagnosed between 2000 and 2018 were extracted from the SEER database. Similarly, data of patients with myofibroblastic tumor in Nanjing Drum Tower Hospital between May 2016 and March 2022 were collected. Then, we conducted univariate and multivariate Cox analyses to identify independent prognostic parameters to develop the nomogram. The model was evaluated by concordance index (C-index), calibration curve, the area under the curve (AUC), decision curve analysis (DCA), Kaplan-Meier analysis, and subgroup analyses. Seven variables were selected to construct the nomogram. The results of the C-index (0.783), calibration curve, the AUCs, and subgroup analyses demonstrated the accurate predictive capacity and excellent discriminative ability of the nomogram. The DCA of the model indicated its better clinical net benefit than that of the traditional system. Evaluation of the predictive performance of the nomogram revealed the superior sensitivity and specificity of the model and the higher prediction accuracy of the outcomes compared with those of the traditional system. The established nomogram may assist patients in consultation and help physicians in clinical decision-making.

SEX-BASED DIFFERENCES IN DRUG DURABILITY AMONG PATIENTS WITH INFLAMMATORY BOWEL DISEASES

Abstract BACKGROUND With an increasing number of therapeutic options to treat IBD, identification of patient-specific factors predictive of drug efficacy is crucial. Sex has been postulated to play a role in response to therapy with possible proposed mechanisms including sex-based hormones and microbiome and epigenetic differences. However, prior clinical data on drug durability stratified by sex are mixed and limited. METHODS Using the SPARC IBD (Study of a Prospective Adult Research Cohort with Inflammatory Bowel Disease) registry, we analyzed time to drug discontinuation for female versus male patients started on a new IBD medication (including biologic and small molecule therapy) after enrollment between 2016 and August 2022. Drug persistence was examined using Kaplan-Meier plots. A Cox regression model was used to adjust for baseline differences in Crohn’s disease phenotype, rates of perianal disease, and concurrent immunomodulator use. A marginal means/rates model was used to adjust for within-patient correlation given that 252 patients had multiple medication starts. RESULTS A total of 1185 patients were identified with 1492 unique new medication starts (n=830 female, 662 male). In this sample, male patients had more complex Crohn’s disease phenotype and higher rates of perianal disease and concurrent immunomodulator use. No significant difference was seen in 12 month drug therapy survival rates based on sex (67.5% females, 65.7% males). Median drug continuation time was 33.5 months in females (95% CI 25.8, 37.4) and 24.5 months in males (95% CI 20.3, 32.8). No difference was seen in anti-TNF and small molecule subgroup analyses. Cox model adjusted for baseline differences in disease severity showed no significant different in probability of drug discontinuation per unit time in females compared to males [HR (95% CI) = 0.95 (0.75-1.21)]. CONCLUSION Both males and females have similar rates of IBD drug durability over time. The reasons for drug discontinuation should be explored in further studies as this may aid physicians in clinical decision-making.

An Executive Summary of The Philippine Interim Clinical Practice Guidelines for the Diagnosis and Management of Well Differentiated Thyroid Cancer 2021.

Thyroid cancer is the most common endocrine cancer in the Philippines affecting primarily women in the reproductive age group. Considering the burden of thyroid cancer in the country, the Department of Health (DOH) called for the development of a national clinical practice guideline that would address patient needs, and aid physicians in clinical decision-making while considering therapeutic cost and availability in the local setting. The 2021 guidelines are aimed at providing optimal care to Filipino patients by assisting clinicians in the evaluation of thyroid nodules and management of well differentiated thyroid cancer. A steering committee convened to formulate clinical questions pertaining to the screening and evaluation of thyroid nodules, surgical and post operative management of thyroid cancer, and palliative care for unresectable disease. A technical working group reviewed existing clinical guidelines, retrieved through a systematic literature search, synthesized clinical evidence, and drafted recommendations based on the ADAPTE process of clinical practice guideline development. The consensus panel reviewed evidence summaries and voted on recommendations for the final statements of the clinical practice guidelines. The guidelines consist of clinical questions and recommendations grouped into six key areas of management of well differentiated thyroid cancer: screening, diagnosis, surgical treatment, post operative management, surveillance, and palliative care. The 2021 guidelines for well differentiated cancer could direct physicians in clinical decision making, and create better outcomes for Filipino patients afflicted with the disease. However, patient management should still be governed by sound clinical judgement and open physician-patient communication.

Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19

&lt;abstract&gt;&lt;sec&gt; &lt;title&gt;Objective&lt;/title&gt; &lt;p&gt;The objective of this study was to provide an overview of Decision Support Systems (DSS) applied in healthcare used for diagnosis, monitoring, prediction and recommendation in medicine.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Methods&lt;/title&gt; &lt;p&gt;We conducted a systematic review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines of articles published until September 2022 from PubMed, Cochrane, Scopus and web of science databases. We used KH coder to analyze included research. Then we categorized decision support systems based on their types and medical applications.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Results&lt;/title&gt; &lt;p&gt;The search strategy provided a total of 1605 articles in the studied period. Of these, 231 articles were included in this qualitative review. This research was classified into 4 categories based on the DSS type used in healthcare: Alert Systems, Monitoring Systems, Recommendation Systems and Prediction Systems. Under each category, domain applications were specified according to the disease the system was applied to.&lt;/p&gt; &lt;/sec&gt;&lt;sec&gt; &lt;title&gt;Conclusion&lt;/title&gt; &lt;p&gt;In this systematic review, we collected CDSS studies that use ML techniques to provide insights into different CDSS types. We highlighted the importance of ML to support physicians in clinical decision-making and improving healthcare according to their purposes.&lt;/p&gt; &lt;/sec&gt;&lt;/abstract&gt;

Clinical Practice of Targeted Capture Sequencing to Identify Actionable Alterations in Cholangiocarcinoma.

Simple SummaryGenetic testing promises to provide guidance for early diagnosis and treatment of cholangiocarcinoma (CCA). Due to the different mutation landscapes across populations and the paucity of sequencing data of Chinese patients with CCA, the existing mutation landscape is insufficient to reflect the mutation characteristics of Chinese patients. We retrospectively analyzed 72 Chinese patients with CCA who had received genetic testing of targeted capture sequencing. A total of 2152 somatic mutations were detected in 56 (77.78%, 56/72) patients, of which, the frequently mutated driver genes were TP53, KMT2D, KMT2C, BCOR, APC, BAP1, ARID1A, NF1, PIK3CA, KRAS, and LRP1B. Most mutations were enriched in NRF2, TP53, and TGF-Beta oncogenic signaling pathways and cadherin repeat domain which were associated with intercellular adhesion. We identified 118 novel pathogenic or likely pathogenic somatic mutations and 77 actionable alterations, which provided potential targets for early diagnosis and treatment planning of CCA.The early diagnosis and treatment of cholangiocarcinoma (CCA) remain a challenge worldwide. Genetic testing promises to solve these problems. Due to the different mutation landscapes across populations and the paucity of sequencing data of Chinese patients with CCA, the existing mutation landscape is insufficient to reflect the mutation characteristics of Chinese patients. Thus, we retrospectively analyzed 72 Chinese patients with CCA who had received genetic testing of targeted capture sequencing. A total of 2152 somatic mutations were detected in 56 (77.78%) patients, of which, the frequently mutated driver genes were TP53 (27.78%), KMT2D (23.81%), KMT2C (20.63%), BCOR (18.06%), APC (15.28%), BAP1 (13.89%), ARID1A (12.50%), NF1 (12.50%), PIK3CA (12.50%), KRAS (11.11%), and LRP1B (11.11%). Most mutations were enriched in NRF2, TP53, and TGF-Beta oncogenic signaling pathways and cadherin repeat domains which were associated with intercellular adhesion. Based on cancer-related public databases and multiple protein function prediction algorithms, we identified 118 novel pathogenic or likely pathogenic somatic mutations and 77 actionable alterations. Molecular analysis of tumors from a precision oncology perspective can provide potential targets for early diagnosis and treatment of CCA and assist physicians in clinical decision making.

Evaluation of Epidermal Growth Factor Receptor 2 Status in Gastric Cancer by CT-Based Deep Learning Radiomics Nomogram.

PurposeTo explore the role of computed tomography (CT)-based deep learning and radiomics in preoperative evaluation of epidermal growth factor receptor 2 (HER2) status in gastric cancer.Materials and methodsThe clinical data on gastric cancer patients were evaluated retrospectively, and 357 patients were chosen for this study (training cohort: 249; test cohort: 108). The preprocessed enhanced CT arterial phase images were selected for lesion segmentation, radiomics and deep learning feature extraction. We integrated deep learning features and radiomic features (Inte). Four methods were used for feature selection. We constructed models with support vector machine (SVM) or random forest (RF), respectively. The area under the receiver operating characteristics curve (AUC) was used to assess the performance of these models. We also constructed a nomogram including Inte-feature scores and clinical factors.ResultsThe radiomics-SVM model showed good classification performance (AUC, training cohort: 0.8069; test cohort: 0.7869). The AUC of the ResNet50-SVM model and the Inte-SVM model in the test cohort were 0.8955 and 0.9055. The nomogram also showed excellent discrimination achieving greater AUC (training cohort, 0.9207; test cohort, 0.9224).ConclusionCT-based deep learning radiomics nomogram can accurately and effectively assess the HER2 status in patients with gastric cancer before surgery and it is expected to assist physicians in clinical decision-making and facilitates individualized treatment planning.