Treatment Decisions For Patients Research Articles

Identification of a novel inflammatory-related gene signature to evaluate the prognosis of gastric cancer patients.

Gastric cancer (GC) is a highly aggressive malignancy with a heterogeneous nature, which makes prognosis prediction and treatment determination difficult. Inflammation is now recognized as one of the hallmarks of cancer and plays an important role in the aetiology and continued growth of tumours. Inflammation also affects the prognosis of GC patients. Recent reports suggest that a number of inflammatory-related biomarkers are useful for predicting tumour prognosis. However, the importance of inflammatory-related biomarkers in predicting the prognosis of GC patients is still unclear. To investigate inflammatory-related biomarkers in predicting the prognosis of GC patients. In this study, the mRNA expression profiles and corresponding clinical information of GC patients were obtained from the Gene Expression Omnibus (GEO) database (GSE66229). An inflammatory-related gene prognostic signature model was constructed using the least absolute shrinkage and selection operator Cox regression model based on the GEO database. GC patients from the GSE26253 cohort were used for validation. Univariate and multivariate Cox analyses were used to determine the independent prognostic factors, and a prognostic nomogram was established. The calibration curve and the area under the curve based on receiver operating characteristic analysis were utilized to evaluate the predictive value of the nomogram. The decision curve analysis results were plotted to quantify and assess the clinical value of the nomogram. Gene set enrichment analysis was performed to explore the potential regulatory pathways involved. The relationship between tumour immune infiltration status and risk score was analysed via Tumour Immune Estimation Resource and CIBERSORT. Finally, we analysed the association between risk score and patient sensitivity to commonly used chemotherapy and targeted therapy agents. A prognostic model consisting of three inflammatory-related genes (MRPS17, GUF1, and PDK4) was constructed. Independent prognostic analysis revealed that the risk score was a separate prognostic factor in GC patients. According to the risk score, GC patients were stratified into high- and low-risk groups, and patients in the high-risk group had significantly worse prognoses according to age, sex, TNM stage and Lauren type. Consensus clustering identified three subtypes of inflammation that could predict GC prognosis more accurately than traditional grading and staging. Finally, the study revealed that patients in the low-risk group were more sensitive to certain drugs than were those in the high-risk group, indicating a link between inflammation-related genes and drug sensitivity. In conclusion, we established a novel three-gene prognostic signature that may be useful for predicting the prognosis and personalizing treatment decisions of GC patients.

Biomarker Turnaround Times and Impact on Treatment Decisions in Patients with Advanced Non-Small Cell Lung Carcinoma at a Large Canadian Community Hospital with an Affiliated Regional Cancer Centre.

Background: Timely reporting of molecular biomarkers is critical in guiding optimal treatment decisions in patients with advanced non-small cell lung carcinoma (NSCLC). Any delays along the tissue or treatment pathway may be associated with suboptimal treatment/outcomes and a reduced quality of life. For many centres, biomarkers are tested off-site. Methods: A retrospective chart review of 123 patients with advanced NSCLC seen between 1 June 2021 and 30 June 2022 was conducted. With a focus on core biomarkers (PD L1, EGFR, and ALK), the outcome variables were as follows: total turnaround time (total TAT), divided into pre-laboratory, laboratory, and post-laboratory time intervals, as well as time to treatment decision (TOTD) and time to optimal systemic therapy decision (TOTSD). Results: At first consult, only 20.3% of patients had all core biomarker results available. The median total TAT was significantly longer for non-squamous (non-SCC) than squamous cell carcinoma (SCC) specimens (36.5 versus 22 days, p < 0.001). The median pre-laboratory time for the entire cohort was 5 calendar days. The median laboratory testing time was greater for non-SCC compared to the SCC specimens (23 versus 12 days, p < 0.001). The median time from consult to TOTD was 19 calendar days for the entire cohort. Conclusions: This study emphasizes the need for the expansion of regional resources to meet the clinical needs of advanced NSCLC patients treated at a regional cancer centre which uses an off-site molecular laboratory.

Timing of first abdominal operation in Crohn’s disease based on a diagnostic model

This study aims to develop a clinical diagnostic model for assessing the need for initial abdominal surgery in patients diagnosed with Crohn's disease (CD) and create a nomogram to facilitate clinical decision-making. A total of 164 surgical CD patients and 230 control CD patients were included in this retrospective analysis. Least Absolute Shrinkage and Selection Operator (Lasso) regression and binomial logistic regression were employed to select clinical variables. The 394 CD patients were randomly allocated to a training set and a validation set in a 7:3 ratio. The filtered variables were used to establish a diagnostic model and nomogram in the training set, subsequently validated in the testing set. Decision Curve Analysis (DCA) and clinical impact curve were constructed to validate the clinical applicability of the model. Binomial logistic regression analysis identified seven clinical variables with a p-value less than 0.01, including Biomarker (B), Waist-to-Height Ratio (WHtR), Intestinal obstruction, Albumin (ALB), Crohn's Disease Activity Index (CDAI), Myocardial Flow Index (MFI), and C-reactive protein (CRP). These variables were utilized to establish the diagnostic model. Calibration curves showed good alignment, with a C-index of 0.996 in the training set and 0.990 in the testing set. DCA and clinical impact curve demonstrated that the diagnostic model had good clinical efficiency and could provide clinical benefits. A validated diagnostic model for determining the timing of the first abdominal operation in CD patients was established and evaluated, showing high discriminative ability, calibration, and clinical efficiency. It can be utilized by clinicians to assess the optimal timing for transitioning CD patients from medical treatment to surgical intervention, providing valuable references for individualized treatment decisions for CD patients.

Navigating colorectal cancer prognosis: A Treg-related signature discovered through single-cell and bulk transcriptomic approaches.

The significance of regulatory T cells (Tregs) in colorectal cancer is unclear. The single-cell sequencing data for colorectal cancer, specifically GSE132465 and GSE188711, were retrieved from the GEO database. Simultaneously, bulk transcriptome data were obtained from the UCSC Xena website. To delve into the heterogeneity of Treg cells and identify key genes at the single-cell sequencing level, we employed dimensionality reduction techniques alongside clustering and conducted differential expression gene analysis. For the bulk transcriptome data, we utilized weighted co-expression network analysis to investigate critical gene modules. Additionally, we employed COX regression and Lasso regression methodologies to construct prognostic models, thereby assessing patient outcomes. To facilitate outcome evaluation, nomograms were constructed. The integration of these diverse approaches aims to comprehensively study colorectal cancer, encompassing single-cell heterogeneity, key gene identification, and prognosis modeling using both single-cell and bulk transcriptome data. Polymerase chain reaction (PCR) experiments are used to verify mRNA expression levels of key genes. The analysis software was R software (version 4.3.2). Through single-cell sequencing analysis and bulk transcriptome analysis, we constructed a prognostic model composed with Treg-associated signatures. The high-risk group demonstrated significantly worse prognosis compared with the low-risk group, highlighting the clinical relevance of our models. PCR confirmed that the key gene DEAH-box helicase 15 (DHX15) was significantly overexpressed in colorectal cancer. The prognostic models developed in this study offer a potential tool for risk assessment, guiding treatment decisions for colorectal cancer patients.

Clinically relevant gene signatures provide independent prognostic information in older breast cancer patients

BackgroundThe clinical utility of gene signatures in older breast cancer patients remains unclear. We aimed to determine signature prognostic capacity in this patient subgroup.MethodsResearch versions of the genomic grade index (GGI), 70-gene, recurrence score (RS), cell cycle score (CCS), PAM50 risk-of-recurrence proliferation (ROR-P), and PAM50 signatures were applied to 39 breast cancer datasets (N = 9583). After filtering on age ≥ 70 years, and the presence of estrogen receptor (ER) and survival data, 871 patients remained. Signature prognostic capacity was tested in all (n = 871), ER-positive/lymph node-positive (ER + /LN + , n = 335) and ER-positive/lymph node-negative (ER + /LN−, n = 374) patients using Kaplan–Meier and multivariable Cox-proportional hazard (PH) modelling.ResultsAll signatures were statistically significant in Kaplan–Meier analysis of all patients (Log-rank P < 0.001). This significance remained in multivariable analysis (Cox-PH, P ≤ 0.05). In ER + /LN + patients all signatures except PAM50 were significant in Kaplan–Meier analysis (Log-rank P ≤ 0.05) and remained so in multivariable analysis (Cox-PH, P ≤ 0.05). In ER + /LN− patients all except RS were significant in Kaplan–Meier analysis (Log-rank P ≤ 0.05) but only the 70-gene, CCS, ROR-P, and PAM50 signatures remained so in multivariable analysis (Cox-PH, P ≤ 0.05).ConclusionsWe found that gene signatures provide prognostic information in survival analyses of all, ER + /LN + and ER + /LN- older (≥ 70 years) breast cancer patients, suggesting a potential role in aiding treatment decisions in older patients.

The effect of urgent-start peritoneal dialysis and urgent-start hemodialysis on clinical outcomes in patients with chronic kidney disease: an updated systematic review and meta-analysis.

Recently, urgent-start peritoneal dialysis (PD) has been suggested in place of urgent-start hemodialysis (HD) in cases of chronic kidney disease (CKD). However, the comparative effectiveness of these methods is still unclear. This study compared the outcomes of urgent-start PD and urgent-start HD in CKD patients. Electronic searches were conducted in PubMed, EMbase, Google Scholar databases, and Cochrane Library, up to 30th July 2023 for studies reporting data on all-cause mortality. Secondary outcomes included dialysis-related infectious and mechanical complications. Risk ratios (RRs) with 95% confidence interval (CI) were calculated. Nine eligible studies involving 941 PD and 779 HD patients were analyzed. Pooled analysis demonstrated elevated risk of all-cause mortality (RR: 1.06, 95% CI: 1.02 to 1.09), dialysis-related infectious complications (RR: 1.05, 95% CI: 1.02 to 1.07), and mechanical complications (RR: 1.08, 95% CI: 1.04 to 1.13) in patients undergoing urgent-start HD than in patients on urgent-start PD. Our findings indicate that CKD patients that received urgent-start HD are at increased risk of all-cause mortality and infectious, and mechanical complications that are associated with the dialysis than patients that received urgent-start PD. These findings have to be considered when making treatment decisions for patients with acute kidney injury. Better understanding of the mechanism of these differences may help to create guidelines for more informed clinical practices.

Type 2 diabetes and inflammatory bowel disease: a bidirectional two-sample Mendelian randomization study

To investigate the association between T2DM and IBD by bidirectional two-sample Mendelian randomization (MR) to clarify the casual relationship. Independent genetic variants for T2DM and IBD were selected as instruments from published genome-wide association studies (GWAS), mainly in European ancestry. Instrumental variables (IVs) associated with T2DM and IBD were extracted separately from the largest GWAS meta-analysis. MR analyses included inverse variance weighting, weighted median estimator, MR Egger regression, and sensitivity analyses with Steiger filtering and MR PRESSO. In the data samples for Ulcerative colitis (UC) (6968 cases, 20,464 controls) and Crohn's disease (CD) (5956 cases, 14,927 controls), there was a negative causal relationship between T2DM and UC [IVW, OR/95%CI: 0.882/(0.826,0.942), p < 0.001]. However, the causal relationships between T2DM and CD, UC and T2DM, CD and T2DM were not significant, and the p value measured by the IVW method was ≥ 0.05. All SNPs showed no significant horizontal pleiotropy (p > 0.05). The results of the bidirectional MR Study suggest that T2DM has a negative causal effect on UC, which provides implications for clinical treatment decisions in IBD patients with T2DM. The findings do not support a causal relationship between T2DM and CD, UC and T2DM, or CD and T2DM, and the impact of IBD on T2DM needs further investigation.

Direct three-dimensional segmentation of prostate glands with nnU-Net.

In recent years, we and others have developed non-destructive methods to obtain three-dimensional (3D) pathology datasets of clinical biopsies and surgical specimens. For prostate cancer risk stratification (prognostication), standard-of-care Gleason grading is based on examining the morphology of prostate glands in thin 2D sections. This motivates us to perform 3D segmentation of prostate glands in our 3D pathology datasets for the purposes of computational analysis of 3D glandular features that could offer improved prognostic performance. To facilitate prostate cancer risk assessment, we developed a computationally efficient and accurate deep learning model for 3D gland segmentation based on open-top light-sheet microscopy datasets of human prostate biopsies stained with a fluorescent analog of hematoxylin and eosin (H&E). For 3D gland segmentation based on our H&E-analog 3D pathology datasets, we previously developed a hybrid deep learning and computer vision-based pipeline, called image translation-assisted segmentation in 3D (ITAS3D), which required a complex two-stage procedure and tedious manual optimization of parameters. To simplify this procedure, we use the 3D gland-segmentation masks previously generated by ITAS3D as training datasets for a direct end-to-end deep learning-based segmentation model, nnU-Net. The inputs to this model are 3D pathology datasets of prostate biopsies rapidly stained with an inexpensive fluorescent analog of H&E and the outputs are 3D semantic segmentation masks of the gland epithelium, gland lumen, and surrounding stromal compartments within the tissue. nnU-Net demonstrates remarkable accuracy in 3D gland segmentations even with limited training data. Moreover, compared with the previous ITAS3D pipeline, nnU-Net operation is simpler and faster, and it can maintain good accuracy even with lower-resolution inputs. Our trained DL-based 3D segmentation model will facilitate future studies to demonstrate the value of computational 3D pathology for guiding critical treatment decisions for patients with prostate cancer.

Genetic mutation profiling reveals biomarkers for targeted therapy efficacy and prognosis in non-small cell lung cancer

IntroductionThe genetic heterogeneity of non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations may affect clinical responses and outcomes to EGFR tyrosine kinase inhibitors (EGFR-TKIs). This study aims to investigate the genomic factors that influence the efficacy and clinical outcomes of first-line, second-line and third-line treatments in NSCLC and explore the heterogeneity of resistance mechanisms. Materials and methodsThis real-world study comprised 65 patients with EGFR mutant NSCLC. Molecular alterations were detected using a customized DNA panel before and after administering targeted therapy. The efficacy and prognosis of each treatment line were evaluated. ResultsIn first-generation EGFR-TKIs treatment, gefitinib showed favorable efficacy compared to icotinib and erlotinib, particularly in patients with EGFR L858R mutations. The resistance mechanisms to first-generation EGFR-TKIs varied among different EGFR mutation cohorts and different first-generation EGFR-TKIs. In second-line EGFR-TKIs treatment, EPH receptor A3 (EPHA3), IKAROS family zinc finger 1 (IKZF1), p21 (RAC1) activated kinase 5 (PAK5), DNA polymerase epsilon, catalytic subunit (POLE), RAD21 cohesin complex component (RAD21) and RNA binding motif protein 10 (RBM10) mutations were markedly associated with poorer progression-free survival (PFS). Notably, EPHA3, IKZF1 and RBM10 were identified as independent predictors of PFS. The mechanisms of osimertinib resistance exhibited heterogeneity, with a higher proportion of non-EGFR-dependent resistant mutations. In third-line treatments, the combination of osimertinib and anlotinib demonstrated superior efficacy compared to other regimens. Glutamate ionotropic receptor NMDA type subunit 2A (GRIN2A) mutation was an independent risk indicator of shorter OS following third-line treatments. ConclusionsComprehending the tumor evolution in NSCLC is advantageous for assessing the efficacy and prognosis at each stage of treatment, providing valuable insights to guide personalized treatment decisions for patients.

Imaging to predict early relapses after treatment discontinuation in patients with large vessel giant cell arteritis – A cohort study

ObjectivesTo investigate the value of [18F]fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) in predicting relapse after treatment discontinuation in patients with large-vessel giant cell arteritis (LV-GCA). MethodsThis study included patients with LV-GCA whose treatment was discontinued between 2018 and 2023. All patients underwent PET/CT and/or MRI at the time of treatment discontinuation in clinical remission. Qualitative and quantitative PET/CT scores, by measuring standardized uptake values (SUV), and semiquantitative MRI scores of the aorta and supraaortic vessels were compared between patients who relapsed within 4 months after treatment discontinuation and those who did not. ResultsForty patients were included (median age 67.4 years, interquartile range (IQR) 60.8–74.0; 77.5 % females). Eleven patients (27.5 %) relapsed after treatment discontinuation (time to relapse 1.9 months, IQR 1.4–3.3). Patients who relapsed were comparable to those who remained in remission with respect to the presence of active vasculitis on MRI and/or PET/CT (54.5% vs. 58.6 %, p = 1.0), the number of segments with vasculitic findings on MRI (0, IQR 0.0–1.5, vs. 2, IQR 0.0–3.0, p = 0.221) or the highest SUV artery/liver ratio on PET/CT (1.5, IQR 1.4–1.6, vs. 1.3, IQR 1.2–1.6, p = 0.505). The median number of vasculitic segments on PET/CT was 2.5 (IQR 0.5–4.5) in those with vs. 0 (IQR 0.0–1.5, p = 0.085) in those without relapse, and the PET/CT scores 4.5 (IQR 0.75–8.25) vs. 0 (IQR 0.0–3.0, p = 0.172). ConclusionPET/CT or MRI at treatment stop did not predict relapse and may not be suited to guide treatment decisions in patients with LV-GCA in remission.

PET-determined myocardial perfusion and flow in coronary artery disease characterization

Positron emission tomography (PET) myocardial perfusion imaging in conjunction with tracer-kinetic modeling enables the concurrent assessment of myocardial perfusion and regional myocardial blood flow (MBF) of the left ventricle in absolute terms in milliliters per gram per minute (mL/g/min). The non-invasive quantification of MBF during pharmacologically induced hyperemia, at rest, and corresponding myocardial flow reserve (MFR) opens a new avenue for the identification and characterization of classical or endogen type of coronary microvascular dysfunction (CMD) as functional substrate for microvascular angina in patients with non-obstructive coronary artery disease (CAD) and/or no CAD at all. Further, PET-MBF quantification expands the scope of conventional myocardial perfusion imaging from the identification of advanced, and flow-limiting, epicardial CAD to early stages of atherosclerosis and/or CMD. Adding MBF assessment to myocardial perfusion may also reliably unravel diffuse ischemia owing to significant left main stenosis and/or multivessel CAD, commonly confirmed by peak stress transient ischemic cavity dilation of the left ventricle during maximal vasomotor stress compared to rest on gated PET images. Owing to high spatial and contrast resolution in conjunction with photon-attenuation free myocardial perfusion PET images, PET is preferentially used for CAD detection in advanced obesity and women with pronounced breast habitus. With increasing clinical use of cardiac PET perfusion and MBF assessment, individualized, and image-guided cardiovascular treatment decisions in CAD patients is likely to ensue, while its translation into improved cardiovascular outcome remains to be investigated.

Associations Between Systolic Pressure, Vascular Waveform, and Volume Flow with Debridement or Amputation Treatment Decisions in Diabetic Foot Ulcer Patients.

Diabetic foot ulcer disease, affecting 6.3% of the global population, necessitates crucial decisions regarding debridement and amputation, with substantial cost, morbidity, and mortality implications. This study's primary goal is to determine effective vascular examination modalities, including systolic blood pressure, vascular waveforms, and blood volume flow to guide optimal treatments for diabetic foot patients. This cross-sectional study at Cipto Mangunkusumo General Hospital aimed to identify effective vascular examination modalities, such as systolic blood pressure, vascular waveforms, and blood volume flow, to guide treatment choices for diabetic foot patients. The study included 38 subjects, equally split between debridement and amputation groups. Notably, the presence of a biphasic pattern in popliteal artery vascular examinations was associated with the decision for amputation in diabetic foot patients (p < 0.05). The Chi-square test revealed that a biphasic ultrasound pattern served as a predictive factor for amputation among diabetic foot patients, with three times more biphasic patients choosing amputation over debridement. Conversely, assessments of popliteal artery systolic pressure, common femoral artery waveform, popliteal artery volume flow, and common femoral artery volume flow showed no significant correlations with the choice of debridement or amputation treatment for diabetic foot patients. In summary, ultrasound assessment of vascular waveform in the popliteal artery emerges as a predictive factor for amputation or debridement in diabetic foot patients.

Universal Digital High-Resolution Melt Analysis for the Diagnosis of Bacteremia

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires approximately 15 hours to detect the presence of a pathogen. We, therefore, assessed the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 17 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 88% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1-mL sample input and sample-to-answer time of 6 hours. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection.

Safety and Diagnostic Efficacy of Image-Guided Biopsy of Small Renal Masses.

Image-guided renal mass biopsy is gaining increased diagnostic acceptance, but there are limited data concerning the safety and diagnostic yield of biopsy for small renal masses (≤4 cm). This study evaluated the safety, diagnostic yield, and management after image-guided percutaneous biopsy for small renal masses. A retrospective IRB-approved study was conducted on patients who underwent renal mass biopsy for histopathologic diagnosis at a single center from 2015 to 2021. Patients with a prior history of malignancy or a renal mass >4 cm were excluded. Descriptive statistics were used to summarize patient demographics, tumor size, the imaging modality used for biopsy, procedure details, complications, pathological diagnosis, and post-biopsy management. A biopsy was considered successful when the specimen was sufficient for diagnosis without need for a repeat biopsy. Complications were graded according to the SIR classification of adverse events. A chi-squared test (significance level set at p ≤ 0.05) was used to compare the success rate of biopsies in different lesion size groups. A total of 167 patients met the inclusion criteria. The median age was 65 years (range: 26-87) and 51% were male. The median renal mass size was 2.6 cm (range: one-four). Ultrasound was solely employed in 60% of procedures, CT in 33%, a combination of US/CT in 6%, and MRI in one case. With on-site cytopathology, the median number of specimens obtained per procedure was four (range: one-nine). The overall complication rate was 5%. Grade A complications were seen in 4% (n = 7), consisting of perinephric hematoma (n = 6) and retroperitoneal hematoma (n = 1). There was one grade B complication (0.5%; pain) and one grade D complication (0.5%; pyelonephritis). There was no patient mortality within 30 days post-biopsy. Biopsy was successful in 88% of cases. A sub-group analysis showed a success rate of 85% in tumors <3 cm and 93% in tumors ≥3 cm (p = 0.01). Pathological diagnoses included renal cell carcinoma (65%), oncocytoma (18%), clear cell papillary renal cell tumors (9%), angiomyolipoma (4%), xanthogranulomatous pyelonephritis (1%), lymphoma (1%), high-grade papillary urothelial carcinoma (1%), and metanephric adenoma (1%), revealing benign diagnosis in 30% of cases. The most common treatment was surgery (40%), followed by percutaneous cryoablation (22%). In total, 37% of patients were managed conservatively, and one patient received chemotherapy. This study demonstrates the safety and diagnostic efficacy of image-guided biopsy of small renal masses. The diagnostic yield was significantly higher for masses 3-4 cm in size compared to those <3 cm. The biopsy results showed a high percentage of benign diagnoses and informed treatment decisions in most patients.

How do surrogates make treatment decisions for patients with dementia: An experimental survey study.

Despite the growing need for surrogate decision-making for older adults, little is known about how surrogates make decisions and whether advance directives would change decision-making. We conducted a nationally representative experimental survey that cross-randomized cognitive impairment, gender, and characteristics of advance care planning among hospitalized older adults through a series of vignettes. Our study yielded three main findings: first, respondents were much less likely to recommend life-sustaining treatments for patients with dementia, especially after personal exposure. Second, respondents were more likely to ignore patient preferences for life-extending treatment when the patient had dementia, and choose unwanted life-extending treatments for patients without dementia. Third, in scenarios where the patient's wishes were unclear, respondents were more likely to choose treatments that matched their own preferences. These findings underscore the need for improved communication and decision-making processes for patients with cognitive impairment and highlight the importance of choosing a surrogate decision-maker with similar treatment preferences.

Using tumor habitat-derived radiomic analysis during pretreatment 18F-FDG PET for predicting KRAS/NRAS/BRAF mutations in colorectal cancer

BackgroundTo investigate the association between Kirsten rat sarcoma viral oncogene homolog (KRAS) / neuroblastoma rat sarcoma viral oncogene homolog (NRAS) /v-raf murine sarcoma viral oncogene homolog B (BRAF) mutations and the tumor habitat-derived radiomic features obtained during pretreatment 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in patients with colorectal cancer (CRC).MethodsWe retrospectively enrolled 62 patients with CRC who had undergone 18F-FDG PET/computed tomography from January 2017 to July 2022 before the initiation of therapy. The patients were randomly split into training and validation cohorts with a ratio of 6:4. The whole tumor region radiomic features, habitat-derived radiomic features, and metabolic parameters were extracted from 18F-FDG PET images. After reducing the feature dimension and selecting meaningful features, we constructed a hierarchical model of KRAS/NRAS/BRAF mutations by using the support vector machine. The convergence of the model was evaluated by using learning curve, and its performance was assessed based on the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis. The SHapley Additive exPlanation was used to interpret the contributions of various features to predictions of the model.ResultsThe model constructed by using habitat-derived radiomic features had adequate predictive power with respect to KRAS/NRAS/BRAF mutations, with an AUC of 0.759 (95% CI: 0.585–0.909) on the training cohort and that of 0.701 (95% CI: 0.468–0.916) on the validation cohort. The model exhibited good convergence, suitable calibration, and clinical application value. The results of the SHapley Additive explanation showed that the peritumoral habitat and a high_metabolism habitat had the greatest impact on predictions of the model. No meaningful whole tumor region radiomic features or metabolic parameters were retained during feature selection.ConclusionThe habitat-derived radiomic features were found to be helpful in stratifying the status of KRAS/NRAS/BRAF in CRC patients. The approach proposed here has significant implications for adjuvant treatment decisions in patients with CRC, and needs to be further validated on a larger prospective cohort.

Valuable interaction with cognitive remediation and optimal antipsychotics for recovery in schizophrenia (VICTORY-S): study protocol for an interventional, open-label, randomized comparison of combined treatment with cognitive remediation and lurasidone or paliperidone.

Cognitive impairment, a core feature of schizophrenia, is associated with poor outcomes. Pharmacotherapy and psychosocial treatment, when used alone, have inadequate effect sizes for cognitive impairment, leading to recent interest in combination interventions. A previous study examined the additive effect of cognitive remediation on lurasidone in patients with schizophrenia, which was negative. Although improvement in cognitive function was suggested for lurasidone, it was inconclusive because there was no antipsychotic control in the study. To clarify whether lurasidone has a meaningful impact on cognitive function in combination with cognitive remediation, we use paliperidone as a control antipsychotic in this study. We hypothesize that combination with lurasidone will improve cognitive and social function to a greater extent than paliperidone. The valuable interaction with cognitive remediation and optimal antipsychotics for recovery in schizophrenia study is a multicenter, interventional, open-label, rater-blind, randomized comparison study, comparing the effect of lurasidone plus cognitive remediation with that of paliperidone plus cognitive remediation in patients with schizophrenia. The Neuropsychological Educational Approach to Remediation (NEAR) is used for cognitive remediation. Eligible patients will be randomized 1:1 to receive lurasidone or paliperidone combined with NEAR (6 weeks antipsychotic alone followed by 24 weeks combination antipsychotic plus NEAR). The primary endpoint is the change from baseline in the tablet-based Brief Assessment of Cognition in Schizophrenia composite T-score at the end of the NEAR combination treatment period. Secondary endpoints will include change from baseline in social function, schizophrenia symptoms, and quality of life at the end of the NEAR combination treatment period. Furthermore, change from baseline to the end of the pharmacotherapy period and change from the end of the pharmacotherapy period to the end of the NEAR combination treatment period will be assessed for all endpoints. Safety will also be evaluated. Achievement of adequate cognitive function is central to supporting social function, which is a key treatment goal for patients with schizophrenia. We think this study will fill in the gaps of the previous study and provide useful information regarding treatment decisions for patients with schizophrenia. Japan Registry of Clinical Trials ID, jRCTs031200338.

A novel nomogram and recursive partitioning analysis for predicting cancer-specific survival of patients with subcutaneous leiomyosarcoma

Accurately predicting prognosis subcutaneous leiomyosarcoma (LMS) is crucial for guiding treatment decisions in patients. The objective of this study was to develop prediction models for cancer-specific survival (CSS) in patients with subcutaneous LMS. The collected cases of diagnosed subcutaneous LMS were randomly divided into a training cohort and a validation cohort at a 6:4 ratio based on tumor location and histological code. The X-tile program was utilized to determine the optimal cutoff points for age index. Univariate and Cox multivariate regression analyses were conducted to identify independent risk factors for subcutaneous LMS patients. Nomograms were constructed to predict CSS, and their performance was assessed using C-index and calibration plots. Additionally, a decision tree model was established using recursive partitioning analysis to determine the total score for CSS prediction in subcutaneous LMS patients based on the nomogram model. A total of 1793 patients with subcutaneous LMS were found. X-tile software divides all patients into ≤ 61 years old, 61–82 years old, and ≥ 82 years old. The most important anatomical sites were the limbs (including the upper and lower limbs, 48.0%). Only 6.2% of patients received chemotherapy, while 44% had a history of radiotherapy and 92.9% underwent surgery. The independent risk factors for patients with subcutaneous LMS were age, summary stage, grade, and surgery. CSS was significantly decreased in patients with distant metastases, which showed the highest independent risk predictor (HR 4.325, 95% CI 3.010–6.214, p < 0.001). The nomogram prediction model of LMS was constructed based on four risk factors. The C-index for this model was 0.802 [95% CI 0.781–0.823] and 0.798 [95% CI 0.768–0.829]. The training cohort's 3-, 5-, and 10-year AUCs for CSS in patients with subcutaneous LMS were 0.833, 0.830, and 0.859, and the validation cohort's AUC for predicting CSS rate were 0.849, 0.830, and 0.803, respectively. Recursive segmentation analysis divided patients into 4 risk subgroups according to the total score in the nomogram, including low-risk group < 145, intermediate-low-risk group ≥ 145 < 176, intermediate-high-risk group ≥ 176 < 196, and high-risk group ≥ 196; The probability of the four risk subgroups is 9.1%, 34%, 49%, and 79% respectively. In this retrospective study, a novel nomogram or corresponding risk classification system for patients with subcutaneous LMS were developed, which may assist clinicians in identifying high-risk patients and in guiding the clinical decision.

Evidence of MRI image features and inflammatory biomarkers association with low back pain in patients with lumbar disc herniation

BACKGROUND CONTEXTWhile MRI image features and inflammatory biomarkers are frequently used for guiding treatment decisions in patients with lumbar disc herniation (LDH) and low back pain (LBP), our understanding of the connections between these features and LBP remains incomplete. There is a growing interest in the potential significance of MRI image features and inflammatory biomarkers, both for quantification and as emerging therapeutic tools for LBP. PURPOSETo investigate the evidence supporting MRI image features and inflammatory biomarkers as predictors of LBP and to determine their relationship with pain intensity. STUDY DESIGNProspective cohort study. PATIENT SAMPLEAll consecutive patients with LDH who underwent discectomy surgery at our institution from February 2020 to June 2023 at the author's institution were included. OUTCOME MEASURESMRI image features in discogenic, osseous, facetogenic, and paraspinal muscles, as well as inflammatory biomarkers in serum (including CRP (C-reactive protein), ESR (erythrocyte sedimentation rate), PCT (procalcitonin), TNF (tumor necrosis factor), interleukin-1 beta (IL-1β), and IL-6), and paraspinal muscles (including TNF, IL-1β, IL-6, IL-10, and transforming growth factor beta 1 (TGF-β1)). METHODSA series of continuous patients diagnosed with LDH were categorized into acute LBP (<12 weeks), chronic LBP (≥12 weeks), and nonLBP groups. MRI image features and inflammatory biomarkers relation to pain intensity was assessed using the independent t-test, Chi-squared tests, Spearman rank correlation coefficient, and logistic regression test. RESULTSCompared to the nonLBP group, the chronic LBP group exhibited a higher incidence of intervertebral disc (IVD) degeneration (≥ grade 3) and high-fat infiltration in paraspinal muscles, alongside a significant reduction in the cross-sectional area (CSA) and fatty degeneration of the multifidus muscle. Furthermore, there was a greater expression of IL-6 in serum and TNF in paraspinal muscles in the chronic LBP group and a greater expression of CRP and IL-6 in serum and TNF in paraspinal muscles in the acute LBP group. CSA and fatty degeneration of multifidus muscle were moderately negatively correlated with chronic LBP scores. The expression of TNF and IL-6 in serum and the expression of TNF in the multifidus muscle were moderately correlated with preoperative LBP. IVD degeneration and high-fat infiltration were identified as risk factors for chronic LBP. CONCLUSIONThe results provide evidence that IVD degeneration, high-fat infiltration, and the reduction of CSA in paraspinal muscles were associated with the development of chronic LBP in patients with LDH, and these associations are linked to inflammatory regulation. This deepens our understanding of the etiology and pathophysiology of LBP, potentially leading to improved patient stratification and more targeted interventions.

Low- and high-volume disease in mHSPC, from CHAARTED to PSMA-PET: An international multicenter retrospective study.

44 Background: High-volume disease (HVD) and low-volume disease (LVD) definitions are based on conventional imaging (CI = CT + bone scan (BS)) according to CHAARTED. Volume of disease is associated with overall survival and used for treatment decisions in mHSPC patients. It remains unknown how these definitions transfer to PSMA-PET. Methods: mHSPC patients from 4 international sites who underwent PSMA-PET+BS within a maximum time interval of 100 days and without any new treatment in between were retrospectively included. CHAARTED stratification into HVD/LVD was applied to BS, CT, MRI and PSMA-PET. HVD was defined by the presence of visceral metastases and/or ≥ 4 bone metastases (with ≥ 1 beyond spine / pelvis). EXINIbone 3.4 (EXINI Diagnostics) was used for the automated bone scan index (aBSI) and the number/localization of lesions on BS. The whole-body (WB) PSMA-PET positive tumor volume (PSMA-TV) was obtained using a semi-automatic thresholding method on Affinity 3.0.2 (Hermes Medical Solutions). Results: Fifty-sevenpairs of PSMA-PET/CT+BS were included (median PSA 226.0 (0.2–2840.0 ng/ml). Based on CI, 16/57 patients had CI-HVD (28.1%) and 41/57 CI-LVD (71.9%). Based on PSMA-PET, 25/57 patients had PSMA-HVD (43.9%) and 19/57 PSMA-LVD (33.3%), 13/57 (22.8%) patients had on PSMA-PET no PSMA-positive or only local / N1-disease. Upshift and downshift from CI to PSMA-PET occurred in 22/57 (38.6%): 9/57 (22.0%) patients were upstaged and 13/57 (22.8%) were downstaged by PSMA-PET. The downshifted patients had no PSMA-PET-positive lesion or only in the prostate fossa while CI was M1 disease. The mean WB-PSMA-TV and aBSI were for CI-HVD was 778.2 ml (0.3–3734.0) and 3.8% (0–11.7), for CI-LVD 51.6 ml (0–228.0) and 0.1% (0–0.6), for PSMA-HVD 573.7 ml (7.9–3734.0) and 2.6% (0–11.7) and for PSMA-LVD, 49.4 ml (1.6–228.0) and 0.1% (0–0.6), respectively. Conclusions: Stage migration between LVD and HVD from CI to PSMA-PET occurs both by up- and downstaging. HVD/LVD based on PSMA PET/CT should be redefined based on patients’ outcome.