Guidance For Clinical Decision Research Articles

Multidisciplinary management of adult patients with chylothorax: a consensus statement.

The management of chylothorax remains challenging given the limited evidence and significant heterogeneity in practice. In addition, there are no practical guidelines on the optimal approach to manage this complex condition. We convened an international group of 27 experts from 20 institutions across five countries and four specialties (pulmonary, interventional radiology, thoracic surgery and nutrition) with experience and expertise in managing adult patients with chylothorax. We performed a literature and internet search for reports addressing seven clinically relevant PICO (Patient, Intervention, Comparison and Outcome) questions pertaining to the management of adult patients with chylothorax. This consensus statement, consisting of best practice statements based on expert consensus addressing these seven PICO questions, was formulated by a systematic and rigorous process involving the evaluation of published evidence, augmented with provider experience. Panel members participated in the development of the final best practice statements using the modified Delphi technique. Our consensus statement aims to offer guidance in clinical decision making when managing patients with chylothorax while also identifying gaps in knowledge and informing future research.

Comparison of Weekly Paclitaxel Regimens in Recurrent Platinum-Resistant Ovarian Cancer: A Single Institution Retrospective Study.

Weekly paclitaxel (WP) is a chemotherapeutic cornerstone in the management of patients with platinum-resistant ovarian carcinoma. Multiple WP dosing regimens have been used clinically and studied individually. However, no formal comparison of these regimens is available to provide objective guidance in clinical decision making. The primary objective of this study was to compare the cumulative dose of paclitaxel delivered using 80 mg/m2/week, administered using either a 3 weeks out of 4 (WP3) or a 4 weeks out of 4 (WP4) regimen. The secondary objective was to evaluate the clinical outcomes associated with both regimens, including efficacy and toxicity parameters. Our retrospective cohort comprised 149 patients harboring platinum-resistant ovarian cancer treated at the CHU de Québec from January 2012 to January 2023. WP3 and WP4 reached a similar cumulative dose (1353.7 vs. 1404.2 mg/m2; p = 0.29). No significant differences in the clinical outcomes were observed. The frequency of dose reduction was significantly higher for WP4 than WP3 (44.7% vs. 4.9%; p < 0.01), mainly due to treatment intolerance from toxicity (34.0% vs. 3.9%; p < 0.01). Our data suggest that a WP3 regimen delivers a similar cumulative dose to WP4, hence offering a better tolerability profile without compromising efficacy.

An Assessment of Different Decision Support Software from the Perspective of Potential Drug-Drug Interactions in Patients with Chronic Kidney Diseases.

Chronic kidney disease (CKD) is a multifaceted disorder influenced by various factors. Drug-drug interactions (DDIs) present a notable risk factor for hospitalization among patients with CKD. This study aimed to assess the frequency and attributes of potential DDIs (pDDIs) in patients with CKD and to ascertain the concordance among different Clinical Decision Support Software (CDSS). A cross-sectional study was conducted in a nephrology outpatient clinic at a university hospital. The pDDIs were identified and evaluated using Lexicomp® and Medscape®. The patients' characteristics, comorbidities, and medicines used were recorded. The concordance of different CDSS were evaluated using the Kendall W coefficient. An evaluation of 1121 prescribed medications for 137 patients was carried out. The mean age of the patients was 64.80 ± 14.59 years, and 41.60% of them were male. The average year with CKD was 6.48 ± 5.66. The mean number of comorbidities was 2.28 ± 1.14. The most common comorbidities were hypertension, diabetes, and coronary artery disease. According to Medscape, 679 pDDIs were identified; 1 of them was contraindicated (0.14%), 28 (4.12%) were serious-use alternative, and 650 (9.72%) were interventions that required closely monitoring. According to Lexicomp, there were 604 drug-drug interactions. Of these interactions, 9 (1.49%) were in the X category, 60 (9.93%) were in the D category, and 535 (88.57%) were in the C category. Two different CDSS systems exhibited statistically significant concordance with poor agreement (W = 0.073, p < 0.001). Different CDSS systems are commonly used in clinical practice to detect pDDIs. However, various factors such as the operating principles of these programs and patient characteristics can lead to incorrect guidance in clinical decision making. Therefore, instead of solely relying on programs with lower reliability and consistency scores, multidisciplinary healthcare teams, including clinical pharmacists, should take an active role in identifying and preventing pDDIs.

Construction and validation of a nomogram for predicting remission of migraine patients with patent foramen ovale after closure

ObjectiveThis study aimed to construct and validate a nomogram model that predicts the remission of migraine attacks by screening factors that affect the prognosis of migraine patients with patent foramen ovale (PFO) after closure. MethodRetrospective analysis was conducted in migraine patients with PFO who underwent PFO closure in the Department of Cardiology of Jiangsu Province Hospital from September 2020 to April 2023. Based on the Migraine Disability Assessment (MIDAS) scores from the 1-year follow-up after PFO closure, all patients who met the inclusion criteria were categorized into a remission group and a non-remission group. The primary efficacy endpoint was remission of migraine headache. After collecting clinical data, transcranial doppler sonography (TCD) results and MIDAS scores, LASSO (least absolute shrinkage and selection operator) regression and multivariable logistic regression analysis were used to filter variables predictive to migraine remission and construct the nomogram model. The Nomogram's accuracy and consistency were respectively assessed through Receiver Operating Characteristic (ROC) curves and calibration curves. Additionally, an analysis of decision curves (DCA) was conducted to evaluate the clinical utility of this newly developed model. ResultA total of 241 consecutive patients were included in the study. The remission group included 21 males and 93 females, with a median age of 39 (30.25,50) years. The non-remission group included 26 males and 101 females, with a median age of 35 (25.5,47.5) years. All Patients were randomly divided into a training cohort and a validation cohort. Multivariable logistic regression analysis showed that 5 independent predictors, including MIDAS before closure (p = 0.0002), mitigating factors (p = 0.0057), number of attacks/month (p = 0.0058), TCD (p = 0.0093) and Platelet Crit (PCT) (p = 0.0351), played a significant role in the prediction of remission of migraine patients with PFO after closure. Based on these independent predictors, the predictive nomogram model of migraine remission in PFO patients was constructed. The application of the nomogram in the training cohort exhibited good discrimination (area under the ROC curve was 0.7763[95% CI 0.7108–0.8418]), which was confirmed in the validation cohort (AUC was 0.704[95% CI 0.5533–0.8547]). The calibration curve showed that the nomogram model demonstrated good calibration performance. Additionally, the decision curve analysis indicated the clinical utility of the nomogram model. ConclusionThe construction of the nomogram model had a considerable predictive accuracy for migraine remission in patients after PFO closure, which may provide constructive guidance for clinical decision making.

Identification of Fatty Acid Metabolism-Related Subtypes in Gastric Cancer Aided by Machine Learning.

Gastric cancer, the fifth most common malignant tumor in the world, poses a serious threat to human health. However, the role of fatty acid metabolism (FAM) in gastric cancer remains incompletely understood. We aim to provide guidance for clinical decisions by utilizing public database of gastric adenocarcinoma to establish an FAM-related gene subtypes via machine learning algorithm. The intersection of FMGs from KEGG, Hallmark, and Reactome bioinformatics databases and the DEGs of the TCGA-STAD cohort was used to decompose the gene matrix related to establish FAM-related gene subtypes by NMF. Comparison of immune infiltrating differences between subtypes using ESTIMATE and Cibersort algorithms. The multifactor Cox regression to identify independent risk genes for patient prognosis based on the subtypes. A prognostic model including independent risk genes was built using random survival forest and Cox regression. IHC validation in gastric cancer and adjacent tissues confirmed the above gene expression level. 71 DEGs related to FMGs of STAD were identified, which was used to established the FAM-related gene subtypes, C1 and C2. The immune infiltrating analysis showed that most immune features of C2 were significantly upregulated compared to C1. The independent risk genes were CGβ8, UPK1B, and OR51G based on the subtypes. A gastric cancer prognostic model consisting of independent risk genes was constructed and patients were classified into high-risk and low-risk groups with survival differential analysis. Finally, IHC showed that CGβ8 and UPK1B expression were upregulated in gastric cancer, while OR51G2 did not detect differences in expression. The study developed a machine learning-based gastric cancer prognosis risk model using FMGs. This model effectively stratifies patients according to their risk levels and provides valuable insights for clinical decision-making, enabling accurate evaluation of patient prognosis.

Determinants Affecting the Clinical Implementation of a Molecularly Informed Molecular Tumor Board Recommendation: Experience from a Tertiary Cancer Center.

Molecular Tumor Boards (MTBs) converge state-of-the-art next-generation sequencing (NGS) methods with the expertise of an interdisciplinary team consisting of clinicians, pathologists, human geneticists, and molecular biologists to provide molecularly informed guidance in clinical decision making to the treating physician. In the present study, we particularly focused on elucidating the factors impacting on the clinical translation of MTB recommendations, utilizing data generated from gene panel mediated comprehensive genomic profiling (CGP) of 554 patients at the MTB of the Comprehensive Cancer Center Erlangen, Germany, during the years 2016 to 2020. A subgroup analysis of cases with available follow-up data (n = 332) revealed 139 cases with a molecularly informed MTB recommendation, which was successfully implemented in the clinic in 44 (31.7%) of these cases. Here, the molecularly matched treatment was applied in 45.4% (n = 20/44) of cases for ≥6 months and in 25% (n = 11/44) of cases for 12 months or longer (median time to treatment failure, TTF: 5 months, min: 1 month, max: 38 months, ongoing at data cut-off). In general, recommendations were preferentially implemented in the clinic when of high (i.e., tier 1) clinical evidence level. In particular, this was the case for MTB recommendations suggesting the application of PARP, PIK3CA, and IDH1/2 inhibitors. The main reason for non-compliance to the MTB recommendation was either the application of non-matched treatment modalities (n = 30)/stable disease (n = 7), or deteriorating patient condition (n = 22)/death of patient (n = 9). In summary, this study provides an insight into the factors affecting the clinical implementation of molecularly informed MTB recommendations, and careful considerations of these factors may guide future processes of clinical decision making.

A novel nomogram for prognosis stratification in salvage liver transplantation: a national-wide study with propensity score matching analysis in China.

Salvage liver transplantation (SLT) has been reported to be an efficient treatment option for patients with recurrent hepatocellular carcinoma (HCC) after liver resection (LR). However, for recipients who underwent liver transplantation (LT) due to recurrent HCC after LR in China, the selection criteria are not well established. In this study, data from the China Liver Transplant Registry (CLTR) of 4,244 LT performed from January 2015 to December 2019 were examined, including 3,498 primary liver transplantation (PLT) and 746 SLT recipients. Propensity score matching (PSM) analysis was used to minimize between-group imbalances. The overall survival (OS) and disease-free survival (DFS) between PLT and SLT in recipients fulfilling the Milan or Hangzhou criteria were compared based on the multivariate analysis, nomograms were plotted to further classify the SLT group into low- and high-risk groups. In this study, the 1-, 3- and 5-year OS and DFS of SLT recipients fulfilling Milan criteria (OS, P=0.01; DFS, P<0.001) or Hangzhou criteria (OS, P=0.03; DFS, P=0.003) were significantly reduced when compared to that of PLT group after PSM analysis. Independent risk factors, including preoperative transarterial chemoembolization (TACE), alpha fetoprotein (AFP) level, tumor maximum size and tumor total diameter were selected to draw a prognostic nomogram. The low-risk SLT recipients (1-year, 95.34%; 3-year, 84.26%; 5-year, 77.20%) showed a comparable OS with PLT recipients fulfilling Hangzhou criteria (P=0.107). An optimal nomogram model for prognosis stratification and clinical decision guidance of SLT was established. The low-risk SLT recipients based on the nomograms showed comparable survival with those fulfilling Hangzhou criteria in PLT group.

Antiplatelet Agent Use After Stroke due to Intracerebral Hemorrhage.

This focused update about antiplatelet agents to reduce the high risk of major adverse cardiovascular events after stroke due to spontaneous (nontraumatic) intracerebral hemorrhage (ICH) complements earlier updates about blood pressure-lowering, lipid-lowering, and oral anticoagulation or left atrial appendage occlusion for atrial fibrillation after ICH. When used for secondary prevention in people without ICH, antiplatelet agents reduce the risk of major adverse cardiovascular event (rate ratio, 0.81 [95% CI, 0.75-0.87]) and might increase the risk of ICH (rate ratio, 1.67 [95% CI, 0.97-2.90]). Before 2019, guidance for clinical decisions about antiplatelet agent use after ICH has focused on estimating patients' predicted absolute risks and severities of ischemic and hemorrhagic major adverse cardiovascular event and applying the known effects of these drugs in people without ICH to estimate whether individual ICH survivors in clinical practice might be helped or harmed by antiplatelet agents. In 2019, the main results of the RESTART (Restart or Stop Antithrombotics Randomized Trial) randomized controlled trial including 537 survivors of ICH associated with antithrombotic drug use showed, counterintuitively, that antiplatelet agents might not increase the risk of recurrent ICH compared to antiplatelet agent avoidance over 2 years of follow-up (12/268 [4%] versus 23/268 [9%]; adjusted hazard ratio, 0.51 [95% CI, 0.25-1.03]; P=0.060). Guidelines in the United States, Canada, China, and the United Kingdom and Ireland have classified the level of evidence as B and indicated that antiplatelet agents may be considered/reasonable after ICH associated with antithrombotic agent use. Three subsequent clinical trials have recruited another 174 participants with ICH, but they will not be sufficient to determine the effects of antiplatelet therapy on all major adverse cardiovascular events reliably when pooled with RESTART. Therefore, ASPIRING (Antiplatelet Secondary Prevention International Randomized Study After Intracerebral Hemorrhage) aims to recruit 4148 ICH survivors to determine the effects of antiplatelet agents after ICH definitively overall and in subgroups.

Different roles of microbiota and genetics in the prediction of treatment response in major depressive disorder

The roles of gut microbiota and susceptibility genes in patients with major depression disorder (MDD) are not well understood. Examining the microbiome and host genetics might be helpful for clinical decision-making. Patients with MDD were recruited in this study and subsequently treated for eight weeks. We identified the differences between the population with a response after two weeks and those with a response after eight weeks. The factors that were significantly correlated with efficacy were used to predict the treatment response. The differences in the importance of microbiota and genetics in prediction were analyzed. Our study identified rs58010457 as a potentially key locus affecting the treatment effect. Different microbiota and enriched pathways might play different roles in the response after two and eight weeks. We found that the area under the curve (AUC) value was greater than 0.8 for both random forest models. The contribution of different components to the AUC was evaluated by removing genetic information, microbiota abundance, and pathway data. The gut microbiome was an important predictor of the response after eight weeks, while genetics was an important predictor of the response after two weeks. These results suggested a dynamic effect of interaction among genetics and gut microbes on treatment. Furthermore, these results provide new guidance for clinical decisions: in cases of inadequate treatment effects after two weeks, the composition of the intestinal flora can be improved by diet therapy, which could ultimately affect the efficacy.

Differing prevalence of microcephaly and macrocephaly in male and female fetuses.

To compare the proportion of female and male fetuses classified as microcephalic (head circumference [HC] < 3rd percentile) and macrocephalic (>97th percentile) by commonly used sex-neutral growth curves. For fetuses evaluated at a single center, we retrospectively determined the percentile of the first fetal HC measurement between 16 and 0/7 and 21-6/7 weeks using the Hadlock, Intergrowth-21st, and NICHD growth curves. The association between sex and the likelihood of being classified as microcephalic or macrocephalic was evaluated with logistic regression. Female fetuses (n = 3,006) were more likely than male fetuses (n = 3,186) to be classified as microcephalic using the Hadlock (0.4% male, 1.4% female; odds ratio female vs. male 3.7, 95% CI [1.9, 7.0], p < 0.001), Intergrowth-21st (0.5% male, 1.6% female; odds ratio female vs. male 3.4, 95% CI [1.9, 6.1], p < 0.001), and NICHD (0.3% male, 1.6% female; odds ratio female vs. male 5.6, 95% CI [2.7, 11.5], p < 0.001) curves. Male fetuses were more likely than female fetuses to be classified as macrocephalic using the Intergrowth-21st (6.0% male, 1.5% female; odds ratio male vs. female 4.3, 95% CI [3.1, 6.0], p < 0.001) and NICHD (4.7% male, 1.0% female; odds ratio male vs. female 5.1, 95% CI [3.4, 7.6], p < 0.001) curves. Very low proportions of fetuses were classified as macrocephalic using the Hadlock curves (0.2% male, < 0.1% female; odds ratio male vs. female 6.6, 95% CI [0.8, 52.6]). Female fetuses were more likely to be classified as microcephalic, and male fetuses were more likely to be classified as macrocephalic. Sex-specific fetal head circumference growth curves could improve interpretation of fetal head circumference measurements, potentially decreasing over- and under-diagnosis of microcephaly and macrocephaly based on sex, therefore improving guidance for clinical decisions. Additionally, the overall prevalence of atypical head size varied using three growth curves, with the NICHD and Intergrowth-21st curves fitting our population better than the Hadlock curves. The choice of fetal head circumference growth curves may substantially impact clinical care.

SUCCESS OF DAIR VERSUS REVISION IN EARLY AND LATE PJIS IN PRIMARY TKA: A PROSPECTIVE STUDY OF 251 CASES

The optimum indications for debridement, antibiotics and implant retention (DAIR) are unclear. Previous studies have demonstrated higher success rate of DAIR within one year of the primary arthroplasty. This study aimed to compare the success rate of DAIR vs revision in “early” and “late” infections to provide guidance for clinical decision making.The Prosthetic Joint Infection in Australia and New Zealand Observational (PIANO) cohort prospectively recorded PJIs between July 2014 and December 2017 in 27 hospitals. This study included PIANO patients with first time PJIs occurring after primary TKA. Treatment success was defined as the patient being alive, free from further revision and without clinical or microbiological evidence of reinfection at two years follow-up.“Early” and “late” infections were analyzed separately. Univariate analysis compared demographic and disease specific factors between the DAIR and Revision groups. Multivariate binary logistic regression identified whether treatment strategy and other risk factors were associated with treatment success in “early” and “late” infections.In 117 “early” (&lt;1 year) infections, treatment success rate was 56% in the DAIR group and 54% in the revision group (p=0.878). No independent risk factors were associated with treatment outcome on multivariate analysis.In 134 “late” (&gt;1 year) infections, treatment success rate was 34.4% in the DAIR group and 60.5% in the revision group (OR 3.07 p=0.006). On multivariate analysis, revision was associated with 2.47x higher odds of success (p=0.041) when compared to DAIR, patients with at least one significant co-morbidity (OR 2.27, p=0.045) or with Staphylococcus aureus PJIs (OR 2.5, p=0.042) had higher odds of failure.In “late” PJIs occurring &gt;1 year following primary TKA, treatment strategy with revision rather than DAIR was associated with greater success. Patients with significant comorbidities and Staphylococcus aureus PJIs were at higher risk of failure regardless of treatment strategy.

Identification of residual disease followed by trade-off analysis between drug optimisation, MRD and sustenance of normal haematopoiesis under maintenance chemotherapy in childhood ALL

ALL, an acute lymphoblastic leukaemia commonly occurring cancer in children, relapses in many cases. Hence to remove (minimal) residual leukaemia or disease (MRD), a maintenance chemotherapy schedule is conducted for two years after intensive chemotherapy. MRD detection occasionally fails due to mutability behaviour of leukemic cells or their aberrant marker expression and presence of MRD in very minor amount enhances the chances of disease relapse in long-term. Application of higher drug dose during maintenance phase could remove MRD but produces drug related toxicity. Bone marrow biopsy is required for MRD detection. Here, a peripheral blood-based control theoretic model is proposed to detect the presence of MRD. Moreover, the model-based eigenvalue and trade-off analysis could provide a guidance in clinical decision making to optimise the maintenance chemotherapeutic regime (both dose and duration) for individual ALL patients.

An improved cell line-derived xenograft humanized mouse model for evaluation of PD-1/PD-L1 blocker BMS202-induced immune responses in colorectal cancer.

The establishment of an in vivo mouse model mimicking human tumor-immune environments provides a promising platform for immunotherapy assessment, drug discovery and clinical decision guidance. To this end, we construct humanized NCG mice by transplanting human hCD34 + hematopoietic progenitors into non-obese diabetic (NOD) Cg- Prkdc scidIL2rg tm1Wjl /Sz (null; NCG) mice and monitoring the development of human hematopoietic and immune systems (Hu-NCG). The cell line-derived xenograft (CDX) Hu-NCG mouse models are set up to assess the outcome of immunotherapy mediated by the small molecule BMS202. As a PD-1/PD-L1 blocker, BMS202 shows satisfactory antitumour efficacy in the HCT116 and SW480 xenograft Hu-NCG mouse models. Mechanistically, BMS202 exerts antitumour efficacy by improving the tumor microenvironment and enhancing the infiltration of hCD8 + T cells and the release of hIFNγ in tumor tissue. Thus, tumor-bearing Hu-NCG mice are a suitable and important in vivo model for preclinical study, particularly in cancer immunotherapy.

Clinical use of 18F-FDG PET/CT in the differential diagnosis of patients with primary and secondary adenoid cystic carcinoma of the lung: a retrospective cohort study.

BackgroundAdenoid cystic carcinoma (ACC) of the lung (ACCL) is a rare malignancy and includes primary ACCL (PACCL) and secondary ACCL (SACCL) metastasized from the ACC of the head and neck. Fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) has been shown to be useful in the differential diagnosis between primary and metastatic lung lesions. This study retrospectively investigated the role of 18F-FDG PET/CT in combination with clinicopathological findings in the management of patients with primary or secondary ACCL.MethodsClinicopathological characteristics and 18F-FDG PET/CT metabolic parameters of 29 patients with PACCL and 11 patients with SACCL with pathological confirmation as gold standard were retrospectively collected. The association between PET/CT metabolic parameters and clinicopathological features was explored. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal maximum standard uptake value (SUVmax) cut-off value to distinguish PACCL from SACCL. The prognostic value of PET/CT metabolic parameters and clinicopathological features was evaluated by Cox regression analysis.ResultsSACCL patients more often presented with multiple ACC lesions in the peripheral lung (81.8% vs. 17.2%, P<0.05) and tended to be asymptomatic compared to patients with PACCL (72.7% versus 27.6%, P<0.05). The SUVmax was significantly higher in PACCL patients compared to SACCL patients (median 4.4 vs. 2.8, P<0.05). Furthermore, at a cut-off value of 3.2 for SUVmax, the sensitivity and specificity of 18F-FDG PET/CT in distinguishing PACCL from SACCL were 82.8% and 72.7%, respectively. Higher SUVmax of ACCL was observed in patients with clinical symptoms, fewer ACC lesions, or larger tumor size (P<0.05). The median PFS of ACCL patients was 71.1 months, and the 12- and 24-month PFS rates were 96.1% and 91.6%, respectively. Univariate Cox regression analysis showed that SACCL from metastasis, lesions located at the peripheral lung or multiple ACC lesions present in the lung, were associated with poorer PFS (P<0.05). However, multivariate Cox regression analysis showed that none of the variables examined were independent predictors of prognosis.ConclusionsThe use of 18F-FDG PET/CT in combination with assessment of clinicopathological features was helpful in distinguishing PACCL from SACCL, which could provide guidance for clinical decision making.

One and Five-Year Mortality Risk Prediction in Patients with Moderate and Severe Aortic Stenosis.

(1) Background: Our goal was to develop a risk prediction model for mortality in patients with moderate and severe aortic stenosis (AS). (2) Methods: All patients aged 40–95 years, with echocardiographic evidence of moderate and severe AS at a single institution, were studied over a median of 2.8 (1.5–4.8) years, between 2013–2018. Patient characteristics and mortality were compared using Chi-squares, t-tests, and Kaplan–Meier (KM) curves, as appropriate. The risk calculation for mortality was derived using the Cox proportional hazards model. A risk score was calculated for each parameter, and the total sum of scores predicted the individualized risks of 1-and 5-year mortality. (3) Results: A total of 1991 patients with severe and 2212 with moderate AS were included. Severe AS patients were older, had a lower ejection fraction %, were more likely to be Caucasian, and had lower rates of obesity and smoking, but had higher rates of cardiac comorbidities and AVR (49.3% vs. 2.8%, p < 0.0001). The unadjusted overall mortality was 41.7% vs. 41%, p = 0.6530, and was not different using KM curves (log rank, p = 0.0853). The models included only patients with complete follow-up (3966 in the 1-year, and 816 in the 5-year model) and included 13 variables related to patient characteristics, degree of AS, and AVR. The C-statistic was 0.75 and 0.72 for the 1-year and the 5-year models, respectively. (4) Conclusions: Patients with moderate and severe AS experience high morbidity and mortality. The usage of a risk prediction model may provide guidance for clinical decision making in complex patients.

Effects of Misoprostol on Induction of Labour in Patients with Hypertensive Disorders of Pregnancy: A Meta-Analysis.

Objective Hypertensive disorders of pregnancy (HDP) can cause serious prenatal and postnatal complications and is a threat to maternal and fetal health. To offer guidance for clinical decisions, we systematically reviewed the effects of misoprostol on induction of labour in HDP patients. Methods PubMed, Web of Science, Embase, CNKI, and Wanfang databases were searched for relevant literature from 2010 to 2020. Subsequently, a meta-analysis was performed to compare the effective rate of induction of labour and reducing postpartum hemorrhage (PPH) between the intervention group (n = 544, misoprostol) and the control group (n = 543, oxytocin). Results A total of 10 studies with 1087 patients were included. The 10 studies compared the effective rate of induction of labour between the two groups and confirmed that the effective rate in the intervention group was significantly higher than that in the control group (OR = 4.37; 95% CI: 2.73, 7.00). Seven studies compared PPH between the groups and showed that it was significantly reduced in the intervention group compared to the control group (SMD = −1.32; 95% CI: −2.05, −0.59; P < 0.0001). Conclusion Misoprostol has a high effective rate of induction of labour in HDP patients and is an effective uterotonic agent in reducing PPH. This meta-analysis provides clinicians with meaningful information to help them make evidence-based decisions.

Clinical Applications of Liquid Biopsy in Prostate Cancer: From Screening to Predictive Biomarker.

Simple SummaryLiquid biopsy (LB), encompassing the analysis of circulating tumor material in the blood or urine, has emerged as a powerful tool in the management of prostate cancer. In localized tumors, LB can distinguish between low- and high-grade cancers and can guide the decision to proceed with or defer tissue biopsy. In advanced disease states, LB has proven prognostic ability in addition to standard-of-care tests like the prostate-specific antigen and has been used in clinical trials to assess response. Certain LB analytes may predict resistance to androgen receptor signaling inhibitors, but how to incorporate their use into everyday clinical decision making remains unclear. Finally, for a minority of patients, LB can identify genomic alterations with significant therapeutic implications. Technological advances and creative uses of LB promise to greatly improve the management of prostate cancer patients in the near future.Prostate cancer (PC) remains the most common malignancy and the second most common cause of cancer death in men. As a result of highly variable biological behavior and development of resistance to available agents under therapeutic pressure, optimal management is often unclear. Traditional surgical biopsies, even when augmented by genomic studies, may fail to provide adequate guidance for clinical decisions as these can only provide a snapshot of a dynamic process. Additionally, surgical biopsies are cumbersome to perform repeatedly and often involve risk. Liquid biopsies (LB) are defined as the analysis of either corpuscular (circulating tumor cells, extracellular vesicles) or molecular (circulating DNA or RNA) tumor-derived material. LB could more precisely identify clinically relevant alterations that characterize the metastatic potential of tumors, predict response to specific treatments or actively monitor for the emergence of resistance. These tests can potentially be repeated as often as deemed necessary and can detect real-time response to treatment with minimal inconvenience to the patient. In the current review, we consider common clinical scenarios to describe available LB assays in PC as a platform to explore existing evidence for their use in guiding decision making and to discuss current limitations to their adoption in the clinic.

Real-world circulating tumor DNA analysis depicts resistance mechanism and clonal evolution in ALK inhibitor-treated lung adenocarcinoma patients

BackgroundSequential treatment with different generations of anaplastic lymphoma kinase (ALK) inhibitors have been widely applied to ALK-positive lung cancer; however, resistance mutations inevitably developed. Further characterization of ALK resistance mutations may provide key guidance to subsequent therapies. Here we explored the emergence of secondary ALK mutations during sequential ALK tyrosine kinase inhibitor (TKI) treatment in a real-world study of Chinese lung adenocarcinoma (ADC) patients.MethodsA clinical-genomic database was queried for lung ADC patients with at least one ALK inhibitor treatment and at least one plasma sample collected following ALK inhibitor treatment. Targeted genome profiling was performed with a 139-gene panel in baseline tumor tissue and serial plasma samples of patients.ResultsA total of 116 patients met inclusion criteria. ALK G1202R was more common in patients with echinoderm microtubule-associated protein-like 4 (EML4)-ALK v3 fusion, whereas ALK L1196M was more common in v1. TP53 mutant patients were significantly associated with harboring multiple ALK resistance mutations (P = 0.03) and v3+/TP53 mutant patients had the highest rate of multiple ALK resistance mutations. The sequential use of ALK TKI led to an increased incidence of concurrent ALK mutations along the lines of therapies. Alectinib had a lower rate (9%) harboring ALK resistance mutation as first-line ALK TKI compared with crizotinib (36%). ALK compound mutations identified included ALK D1203N/L1196M, ALK G1202R/L1196M, and ALK G1202R/F1174C, which may be lorlatinib resistant. Using paired pretreatment and post-treatment samples, we identified several ALK-independent resistance-related genetic alterations, including PTPRD and CNKN2A/B loss, MYC, MYCN and KRAS amplification, and EGFR19del.ConclusionsSequential postprogression plasma profiling revealed that increased lines of ALK inhibitors can accelerate the accumulation of ALK resistance mutations and may lead to treatment-refractory compound ALK mutations. The selection for optimal first-line TKI is very important to achieve a more efficacious long-term strategy and prevent the emergence of on-target resistance, which may provide guidance for clinical decision making.

Dose‐dependent mathematical modeling of interferon‐α‐treatment for personalized treatment of myeloproliferative neoplasms

AbstractLong‐term treatment with interferon‐alfa (IFN) can reduce the disease burden of patients diagnosed with myeloproliferative neoplasms (MPNs). Determining individual patient responses to IFN therapy may allow for efficient personalized treatment, reducing both drop‐out and disease burden. A mathematical model describing hematopoietic stem cells and the immune system is suggested. Considering the bone marrow and the blood allows for modeling disease dynamics both in the absence and presence of IFN treatment. Through comprehensive modeling of the effects of IFN, the model was related to individualized patient‐data consisting of longitudinal hematologic and molecular measurements. Treatment responses were modeled on a population level, allowing for personalized predictions from a single pretreatment data point. Personalized fits were found to agree well with data for individual patients. This allowed for a quantitative description of the treatment response, yielding a mechanistic interpretation of differences from patient to patient. The treatment responses of individual patients were combined and a formulation of treatment responses on the population level was described and simulated. Based on pretreatment data and the actual treatment scheduling, the population‐level response was found to predict the treatment response of particular patients accurately over a five‐year period. Mechanism‐based modeling of treatment effects demonstrates that hematologic and molecular observable quantities can be predicted on the level of individual patients. Personalized patient‐fits suggest that the effect of IFN treatment can be quantified and interpreted through mathematical modeling, despite variation in hematologic and molecular responses between patients. Mathematical modeling suggests that in general both hematologic and molecular markers must be considered to avoid early relapse. Furthermore, personalized model‐fits provide quantitative measures of the hematologic and molecular responses, determining when treatment‐cessation is appropriate. Proof‐of‐concept population‐level modeling of treatment responses from pretreatment data successfully predicted clinical measures for a 5‐year period. We believe that this approach could have direct clinical relevance, offering expert guidance for clinical decisions about IFN treatment of MPN patients.

Retrospective Study of Venous Thromboembolism Prophylaxis Dosing of Heparin in Adult Patients receiving Continuous Renal Replacement Therapy

Background: Appropriate chemical and/or mechanical venous thromboembolism prophylaxis is a high priority for clinicians. Unfortunately, there is little evidence-based guidance for clinical decision making for patients requiring both renal replacement therapy and VTE prophylaxis. The package insert for unfractionated heparin recommends 5000 units subcutaneously every 8 to 12 hours for VTE prophylaxis. Objective: The purpose of this study was to assess the two recommended dosing intervals and determine if there is a difference in terms of incidence of clotting or bleeding events. Methods: 159 patients were admitted to the UNC Health Care system between March 2014 and November 2019 and retrospectively screened for incidence of both the primary composite efficacy outcome (symptomatic or asymptomatic vascular event (VTE [DVT and PE]), ischemic event (stroke, TIA, or myocardial infarction), or death related to coagulopathy), the individual components of the composite outcome and the primary safety outcome. The results of the outcomes were then compared and analyzed using Fischer’s Exact test. Results: The two tailed p-values of the primary composite efficacy outcome (0.3517), the primary safety outcome (0.1571) and each of the composite outcomes (0.1556, 1.0000, 0.2297, respectively) showed no statistically significant difference. Conclusion: Results of this study show that there is no statistical difference between the dosing intervals of prophylactic UFH of every 8 to 12 hours, in terms of the incidence of VTE and major bleed events, for patients requiring CRRT. Suggesting that either interval is both efficacious and safe for the use of VTE prophylaxis.