Heterogeneity In Treatment Response Research Articles

Heterogeneity of treatment response to beta-blockers in the treatment of portal hypertension: A systematic review.

It has been suggested that a relevant proportion of patients do not respond to nonselective beta-blockers (NSBB)s, which raises questions regarding the need for individualized therapy. The existence of potential heterogeneity in the treatment response can be assessed using the variability ratio (VR) of the outcome measurement (in this case, HVPG) between the treated and placebo groups. We conducted a systematic review and meta-analysis of randomized controlled trials to assess the potential heterogeneity in the portal pressure response to NSBBs. After a systematic search, we quantified the heterogeneity of treatment response with the VR between the treatment and control groups, with VR > 1 indicating potential heterogeneity. We used a similar approach to compare carvedilol with propranolol and statins with placebo. We identified 18 studies that included 965 patients. A comparison between beta-blockers and placebo showed a pooled VR of 0.99 (95% CI:0.87-1.14), which suggests a homogeneous HVPG response to NSBB at the individual patient level (ie, no evidence to support that some patients responded to beta-blockers and others did not). For the comparison between carvedilol and propranolol, pooled VR was 0.97 (95% CI 0.82-1.14), suggesting that carvedilol achieves a greater average response (rather than an increase in the proportion of responders). There was no evidence of a heterogeneous response to statins. Our analysis did not support the existence of a heterogeneous patient-by-patient response to NSBBs in cirrhosis. These findings challenge the concept of personalized therapy based on portal pressure response and indicate that routine portal pressure measurement may not be necessary to guide NSBB therapy.

Pharmacotherapy to Improve Cognitive Functioning After Acquired Brain Injury: AMeta-Analysis and Meta-Regression.

Cognitive impairments, common sequelae of acquired brain injury (ABI), significantly affect rehabilitation and quality of life. Currently, there is no solid evidence-base for pharmacotherapy to improve cognitive functioning after ABI, nevertheless off-label use is widely applied in clinical practice. This meta-analysis and meta-regression aims to quantitatively aggregate the available evidence for the effects of pharmacological agents used in the treatment of cognitive impairments following ABI. We conducted a comprehensive search of Embase, Medline Ovid, and Cochrane Controlled Trials Register databases for randomized controlled and crossover trials. Meta-analytic effects were calculated for each pharmaceutical agent and targeted neuromodulator system. Cognitive outcome measures were aggregated across cognitive domains. Of 8,216 articles, 41 studies (4,434 patients) were included. The noradrenergic agent methylphenidate showed a small, significant positive effect on cognitive functioning in patients with traumatic brain injury (TBI; k = 14, d = 0.34, 95% confidence interval: 0.12-0.56, P = 0.003). Specifically, methylphenidate was found to improve cognitive functions related to executive memory, baseline speed, inhibitory control, and variability in responding. The cholinergic drug donepezil demonstrated a large effect size, albeit based on a limited number of studies (k = 3, d = 1.68, P = 0.03). No significant effects were observed for other agents. Additionally, meta-regression analysis did not identify significant sources of heterogeneity in treatment response. Our meta-analysis supports the use of methylphenidate for enhancing cognitive functioning in patients with TBI. Although donepezil shows potential, it warrants further research. These results could guide clinical decision making, inform practice guidelines, and direct future pharmacotherapeutic research in ABI.

Research progress and prospects of artificial intelligence in diagnosis and treatment of colorectal cancer

Colorectal cancer is one of the most common malignant tumors worldwide. Due to the heterogeneity in patient outcomes and treatment responses to standard therapy regimens, personalized diagnostic and therapeutic strategies have remained a focus of sustained interest in research. In recent years, with the rapid progression of artificial intelligence (AI) technology in the medical field, an abundance of phased research results has emerged in the decision-making for preoperative, intraoperative, and postoperative diagnostic and therapeutic plans for colorectal cancer, demonstrating great potential for application. This new and efficient solution provides for the personalized evaluations and auxiliary diagnoses and treatments of patients with colorectal cancer. In the future, AI systems may continue to advance towards multimodal, multi-omics, and real-time directions. This paper aims to explore the current state of research on the multi-faceted auxiliary applications of AI in the diagnosis and treatment of colorectal cancer, as well as to present a prospective view of the innovations that AI technology could bring to personalized colorectal cancer treatment in the future and the challenges it may face.

Heterogeneity in response to treatment across tinnitus phenotypes

The clinical heterogeneity of chronic tinnitus poses major challenges to patient management and prompts the identification of distinct patient subgroups (or phenotypes) that respond more predictable to a particular treatment. We model heterogeneity in treatment response among phenotypes of tinnitus patients concerning their change in self-reported health burden, psychological characteristics, and tinnitus characteristics. Before and after a 7-day multimodal treatment, 989 tinnitus patients completed 14 assessment questionnaires, from which 64 variables measured general tinnitus characteristics, quality of life, pain experiences, somatic expressions, affective symptoms, tinnitus-related distress, internal resources, and perceived stress. Our approach encompasses mechanisms for patient phenotyping, visualizations of the phenotypes and their change with treatment in a projected space, and the extraction of patient subgroups based on their change with treatment. On average, all four distinct phenotypes identified at the pre-intervention baseline showed improved values for nearly all the considered variables following the intervention. However, a considerable intra-phenotype heterogeneity was noted. Five clusters of change reflected variations in the observed improvements among individuals. These patterns of treatment effects were identified to be associated with baseline phenotypes. Our exploratory approach establishes a groundwork for future studies incorporating control groups to pinpoint patient subgroups that are more likely to benefit from specific treatments. This strategy not only has the potential to advance personalized medicine but can also be extended to a broader spectrum of patients with various chronic conditions.

Diffusion tensor imaging in pediatric patients with dystonia

Background: Childhood-onset dystonia is often progressive and severely impairs a child´s life. The pathophysiology is very heterogeneous and treatment responses vary in patients with dystonia. Factors influencing treatment effects remain to be elucidated. We hypothesize that differences in brain connectivity and fiber coherence contribute to the heterogeneity in treatment response among pediatric patients with inherited and acquired dystonia.Methods: Twenty patients with childhood-onset dystonia were retrospectively recruited including twelve patients with inherited or idiopathic, and eight patients with acquired dystonia (mean age 10 years; 8 female/12 male). Fiber density between the internal part of the globus pallidus and selective target regions, as well as the diffusion measures of fractional anisotropy (FA) and mean diffusivity (MD) were analyzed and compared between different etiologies.Results: Patients with acquired dystonia presented higher fiber density to the premotor cortex and putamen and lower FA values in the thalamus compared to patients with inherited/idiopathic dystonia. MD in the premotor cortex was higher in patients with acquired dystonia, while it was lower in the thalamus.Conclusion: Diffusion MRI reveals microstructural and network alterations in patients with dystonia of different etiologies.

Extracting immunological and clinical heterogeneity across autoimmune rheumatic diseases by cohort-wide immunophenotyping

ObjectiveExtracting immunological and clinical heterogeneity across autoimmune rheumatic diseases (AIRDs) is essential towards personalised medicine.MethodsWe conducted large-scale and cohort-wide immunophenotyping of 46 peripheral immune cells using Human Immunology Protocol of...

Mechanism-centric regulatory network identifies NME2 and MYC programs as markers of Enzalutamide resistance in CRPC

Heterogeneous response to Enzalutamide, a second-generation androgen receptor signaling inhibitor, is a central problem in castration-resistant prostate cancer (CRPC) management. Genome-wide systems investigation of mechanisms that govern Enzalutamide resistance promise to elucidate markers of heterogeneous treatment response and salvage therapies for CRPC patients. Focusing on the de novo role of MYC as a marker of Enzalutamide resistance, here we reconstruct a CRPC-specific mechanism-centric regulatory network, connecting molecular pathways with their upstream transcriptional regulatory programs. Mining this network with signatures of Enzalutamide response identifies NME2 as an upstream regulatory partner of MYC in CRPC and demonstrates that NME2-MYC increased activities can predict patients at risk of resistance to Enzalutamide, independent of co-variates. Furthermore, our experimental investigations demonstrate that targeting MYC and its partner NME2 is beneficial in Enzalutamide-resistant conditions and could provide an effective strategy for patients at risk of Enzalutamide resistance and/or for patients who failed Enzalutamide treatment.

Nové perspektivy v bariatricko-metabolické léčbě

Summary: Obesity is a chronic disease that affects millions of people worldwide and is associated with many health complications. The main goal of obesity treatment is to improve health by achieving and maintaining weight loss or through imposing metabolic changes. For treatment, there are several interventions available, such as diet and exercise, drug therapy, surgical procedures. If used as MONO therapy, they often show insufficiency to achieve/maintain adequate weight loss and/or metabolic improvement in long term. Patients seeking low invasive, however still efficient treatment or those with insufficient treatment results or side effects may, under view of new developments both in pharma and surgery, benefit from combined approach of both, anti-obesity medications and very low invasive bariatric-metabolic surgery, such as gastric plication (namely endoscopic plication), partial jejuno-ileal diversion and left gastric artery embolization. There are several new anti-obesity drugs that have been developed or are in development. These drugs target different pathways in the body, such as hormones, neurotransmitters, receptors, enzymes, i.e. to reduce food intake, increase energy expenditure, alter nutrient absorption. In bariatric-metabolic surgery new understanding of the mechanisms of action, which involve not only mechanical restriction or malabsorption, but also neurohormonal modulation, gut microbiome alteration, immune system regulation, and epigenetic changes is being applied to the treatment pathways. For optimal success, heterogeneity of treatment response needs to be incorporated into management plans. Low invasive bariatric-metabolic surgery combined with pharmacotherapy can lead to additive weight-loss benefits and less side effects and it usually works in synergy with medications. Thus, combined approach to obesity treatment that involves anti-obesity medications and BMS are complementary to each other. Laparoscopic PJID seems to be one of the promising non-drug interventions, especially for type 2 diabetic patients with poorly controlled diabetes. Pilot results at two, five and seven years are presented in the article. In 5 years after PJID mean BMI decreased by –12.4%. Mean HbA1c decreased in 2 years after the operation by mean of –2.48 (–32.3%), after 5 years by –3,51 (–45.8%) and in 7 years still decrease of –2.39 (–31.2%) was noted. Glycaemia decreased by mean of –2.5 mmol/l in 2 years, in 5 years postoperatively mean decrease was –4.8 (–44.0%) a in 7 years the mean decrease was – 5.5 mmol/l (–50.4%) in comparison with the pre-op values. Partial jejunal diversion provides an anatomy sparing, low risk, potentially reversible, metabolic procedure, especially in a view of potential use of magnetic approach. The operation does not neccessitate significant alterations in lifestyle, mineral and/or vitamin supplementation and offers rapid recovery. Anti-obesity medications may help prepare patients for bariatric surgery by inducing preoperative weight loss and reducing surgical risk and/or through leveraging treatment outcomes if used in the immediate postoperative period. May also help to prevent or treat weight regain after bariatric surgery by enhancing satiety and reducing hunger. In non-responders to medication before they get surgery may trigger respond to the medication after surgery. New obesity treatment model that utilizes combination of new drugs and low invasive treatment (such as surgical, endoscopic and other new technologies, e.i.magnetic surgery), can enhance and leverage treatment outcomes without increasing risks. Key words: obesity – bariatric-metabolic surgery – pharmacotherapy – combined treatment

Specific gut pathobionts escape antibody coating and are enriched during flares in patients with severe Crohn’s disease

ObjectivePatients with Crohn’s disease (CD) exhibit great heterogeneity in disease presentation and treatment responses, where distinct gut bacteria and immune interactions may play part in the yet unresolved disease aetiology....

Effects of psychotherapy on brain activation during negative emotional processing in patients with posttraumatic stress disorder: a systematic review and meta-analysis.

Post-traumatic stress disorder (PTSD) is a debilitating condition which has been related to problems in emotional regulation, memory and cognitive control. Psychotherapy has a non-response rate of around 50% and understanding the neurobiological working mechanisms might help improve treatment. To integrate findings from multiple smaller studies, we performed the first meta-analysis of changes in brain activation with a specific focus on emotional processing after psychotherapy in PTSD patients. We performed a meta-analysis of brain activation changes after treatment during emotional processing for PTSD with seed-based d mapping using a pre-registered protocol (PROSPERO CRD42020211039). We analyzed twelve studies with 191 PTSD patients after screening 3700 studies. We performed systematic quality assessment both for the therapeutic interventions and neuroimaging methods. Analyses were done in the full sample and in a subset of studies that reported whole-brain results. We found decreased activation after psychotherapy in the left amygdala, (para)hippocampus, medial temporal lobe, inferior frontal gyrus, ventrolateral prefrontal cortex, right pallidum, anterior cingulate cortex, bilateral putamen, and insula. Decreased activation in the left amygdala and left ventrolateral PFC was also found in eight studies that reported whole-brain findings. Results did not survive correction for multiple comparisons. There is tentative support for decreased activation in the fear and cognitive control networks during emotional processing after psychotherapy for PTSD. Future studies would benefit from adopting a larger sample size, using designs that control for confounding variables, and investigating heterogeneity in symptom profiles and treatment response.

Blood‐based biomarkers for predicting treatment response in the Apathy in Dementia Methylphenidate Trial 2 randomized clinical trial

AbstractBackgroundThe Apathy in Dementia Methylphenidate Trial 2 (ADMET 2) found that methylphenidate (MPH) was modestly efficacious is treating apathy in Alzheimer’s disease (AD) with 66% response (> = 4 point decrease on Neuropsychiatric Inventory – apathy (NPI‐A). Here, we evaluated if blood‐based biomarkers potentially associated with treatment‐limiting neuronal damage predicted the probability of treatment response.MethodADMET 2 participants with baseline and endpoint (6 month) NPI‐A and baseline concentrations of (i) neuronal damage: neurofilament light (NFL) and S‐100B, (ii) inflammation: interleukin (IL)‐6, IL‐10, Tumor Necrosis Factor‐alpha (TNFα), and (iii) oxidative stress: lipid hydroperoxide (LPH), 4‐hydroxynonenal (4‐HNE), 8‐isoprostane (8‐ISO) were included. Biomarkers were normalized by log transformation and pareto scaling. Univariate models examined whether each biomarker interacted with the treatment condition to predict a change of at least 2 points on the NPI‐A. Next, biomarkers with significant associations were included in a multivariate logistical regression model that was used to predict treatment response to MPH and placebo. The index score (difference between response probabilities for MPH and placebo) of each participant indicated their favourability for MPH treatment. Participants were grouped into quartiles by their index score with confidence intervals estimated using non‐parametric bootstrapping.ResultForty‐nine participants (placebo = 26, MPH = 23, age = 75.4 years (standard deviation [SD] = 7.6), 57% males, Mini Mental State Examination = 19.7 [SD = 4.6]) were included. MPH was more efficacious than placebo in those with higher baseline NFL (‐5.8, t = ‐3.1, p = 0.003), and less efficacious in those with higher LPH (2.0, t = 1.48, p = 0.15). Apathy worsened in participants with high TNFα (2.71, t = 1.94, p = 0.06) in both MPH and placebo groups. Participants in the top quartile of the biomarker index score (66.7% on MPH) were more likely to respond to MPH than placebo (index score = 0.58, 95%CI: 0.48, 0.69).ConclusionIndividuals with greater neuronal injury were more likely to respond to MPH, suggesting that MPH supplementation provides more benefit when neuronal injury is more severe. Combining blood biomarkers yielded a prediction score where participants with high NFL and low LPH levels were more likely to respond to MPH. This approach utilizes biomarkers to address heterogeneity in treatment response to MPH.

The KIR-HLA-CD16a Immunogenetic Profile Influences NK Cell-Mediated ADCC and Response to Rituximab Therapy in B-Cell Lymphomas

Rituximab-based chemoimmunotherapy (R-CHOP) is the standard of care in most B-cell lymphomas, however there is marked interpatient heterogeneity in treatment response. An important mechanism of Rituximab (anti-CD20) action is through natural killer (NK) cell-mediated antibody-dependent cellular cytotoxicity (ADCC), but the factors influencing this are poorly understood. Here, we present findings from a preclinical study investigating the role of NK cell receptor polymorphisms and HLA allelic variation on ADCC against aggressive B-cell lymphoma cell lines. Genotyping was conducted using Luminex-based SSO and Sanger sequencing. Multicolor flow cytometry was used to assess the response of activated NK cells from healthy donors against 8 lymphoma cell lines. Individuals carrying the GG or GT allele in CD16a were found to have a 3-8 fold greater NK cell response compared to individuals with a TT allele and rituximab-mediated ADCC was significantly greater in individuals with a KIR-3DL1 allele when tested against B-cell lymphomas lacking the HLA-Bw4 allele. An additive effect was observed when considering both CD16a and KIR-HLA together. As expected, CD20 expression was a strong correlate of NK cell response. In summary, NK cell-mediated ADCC in response to ADCC appears to be influenced by the KIR-HLA-CD16a genotype. These findings suggest a potential role for immunogenotyping in B-cell lymphomas treated with Rituximab. Additionally, the presence of the shared F c receptor domain opens the possibility of applying this framework towards predicting NK cell responses to antibody therapies in other diseases.

Asymptotically robust permutation-based randomization confidence intervals for parametric OLS regression

Randomization inference provides exact finite sample tests of sharp null hypotheses which fully specify the distribution of outcomes under counterfactual realizations of treatment, but the sharp null is often considered restrictive as it rules out unspecified heterogeneity in treatment response. However, a growing literature shows that tests based upon permutations of regressors using pivotal statistics can remain asymptotically valid when the assumption regarding the permutation invariance of the data generating process used to motivate them is actually false. For experiments where potential outcomes involve the permutation of regressors, these results show that permutation-based randomization inference, while providing exact tests of sharp nulls, can also have the same asymptotic validity as conventional tests of average treatment effects with unspecified heterogeneity and other forms of specification error in treatment response. This paper extends this work to the consideration of interactions between treatment variables and covariates, a common feature of published regressions, as well as issues in the construction of confidence intervals and testing of subsets of treatment effects.

Assessing the potential for precision medicine of glucose-lowering drugs in type 2 diabetes mellitus: a meta-regression analysis considering body weight variability from 120 randomized trials

Abstract Background Thus far, randomized controlled trials (RCTs) of glucose-lowering drugs reporting on treatment effects on body weight (BW) as cardiovascular risk factor in type 2 diabetes mellitus have not included precision medicine approaches. However, taking into account treatment response heterogeneity, their potential may be analyzed from published data of RCTs using meta-regression analyses. Both treatment response variation and predictors are required conditions for precision medicine to work. Purpose To assess the potential benefits of precision medicine by quantifying the variation of body weight as patient response to treatment, and to identify predictors which could explain this variation. Methods We used four recent systematic reviews on RCTs comparing pharmacological treatment of type 2 diabetes (included but not limited to sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists and thiazolidinediones) to placebo. RCTs reporting on BW at baseline and after follow-up to allow for calculation of its logarithmic standard deviation (Log(SD)) in treatment and placebo groups were included. Meta-regression models accounting for treatment means, differing sample sizes, and correlation across treatment from the same trial were used. A separate meta-regression model to evaluate interactions of treatment and individual predictor variables (age, male sex, pre-randomization BW, duration of disease, duration of treatment, year of study and drug class) was applied. Results 120 randomized trials with a total of 43,663 participants were included. The median BW after treatment was 85.2 kg in the placebo groups and 86.2 kg in the therapy groups. A slightly greater treatment response heterogeneity was shown in the therapy groups with a median Log(SD)=2.83 compared to 2.79 from the placebo. After full adjustment in the meta-regression model the difference in BW Log(SD)s was -0.020 (95% CI: -0.063; 0.022) (Figure 1). Scatter plots adjusted for different sample sizes did not show any interaction (i.e. slope divergence) between predictors and the respective treatment (therapy or placebo). Figure 2 demonstrates this using pre-randomization BW as an example. Conclusions We found no major treatment response heterogeneity in RCTs of glucose-lowering drugs reporting on body weight in type 2 diabetes. In addition, none of the considered predictors were able to explain a potential variation in treatment response. The precision medicine approach may thus be of limited value in this setting.

Precision medicine analysis of heterogeneity in individual-level treatment response to amyloid beta removal in early Alzheimer's disease.

Alzheimer's disease (AD) is a neurological disorder with variability in pathology and clinical progression. AD patients may differ in individual-level benefit from amyloid beta removal therapy. Random forest models were applied to the EMERGE trial to create an individual-level treatment response (ITR) score which represents individual-level benefit of high-dose aducanumab relative to the placebo. This ITR score was used to test the existence of heterogeneity in treatment effect (HTE). We found statistical evidence of HTE in the Clinical Dementia Rating-Sum of Boxes (CDR-SB;P= 0.034). The observed CDR-SB benefit was 0.79 points greater in the group with the top 25% of ITR score compared to the remaining 75% (P=0.020). Of note, the highest treatment responders had lower hippocampal volume, higher plasma phosphorylated tau 181 and a shorter duration of clinical AD at baseline. This ITR analysis provides a proof of concept for precision medicine in future AD research and drug development. Emerging trials have shown a population-level benefit from amyloid beta (Aβ) removal in slowing cognitive decline in early Alzheimer's disease (AD). This work demonstrates significant heterogeneity of individual-level treatment effect of aducanumab in early AD. The greatest clinical responders to Aβ removal therapy have a pattern of more severe neurodegenerative process.

Understanding the Role of Therapist Quality in Accounting for Heterogeneity of Patient Outcomes in Psychosocial Chronic Pain Treatments

A variety of evidence-based psychosocial treatments now exist for chronic pain. However, on average, effect sizes have tended to be modest and there is a high degree of heterogeneity in treatment response. In this focus article, we explore the potential role that therapist quality in delivering treatment may have in accounting for a degree of this variability in outcome. Therapist quality refers to the skillful delivery of treatment, harnessing both specific and common therapeutic factors during sessions. While recognized as important to assess and report in clinical trials by some reporting guidelines, few randomized controlled trials evaluating psychosocial treatments for chronic pain have reported on therapist factors. We reviewed the clinical trials included in three systematic reviews and meta-analyses of trials of cognitive-behavioral therapy (mainly), mindfulness-based interventions, and acceptance and commitment therapy. We found that of the 134 trials included, only nine assessed and reported therapist quality indicators, with a variety of procedures used. This is concerning as without knowledge of the quality in which treatments are delivered, the estimates of effect sizes reported may be misrepresented. We contextualize this finding by drawing on the broader psychotherapy literature which has shown that more skillful, effective therapists demonstrated ten times better patient response rates. Examination of the characteristics associated with these more effective therapists tends to indicate that skillful engagement of common factors in therapy sessions represents a distinguishing feature. We conclude by providing recommendations for assessing and reporting on therapist quality within clinical trials evaluating psychosocial treatments for chronic pain. PerspectiveTherapist quality in the delivery of psychosocial treatments for chronic pain has rarely been assessed in clinical trials. We propose that therapist quality indicators are an under-studied mechanism that potentially contributes to the heterogeneity of treatment outcomes. We provide recommendations for assessing and reporting on therapist quality in future trials.

Distinct long-term disease activity trajectories differentiate early on treatment with etanercept in both rheumatoid arthritis and spondylarthritis patients: a prospective cohort study

To characterize disease activity trajectories and compare long-term drug retention between rheumatoid (RA) and spondylarthritis (SpA) patients initiating tumor necrosis factor inhibitor (TNFi) treatment (etanercept). Prospective observational study of RA, axial (AxSpA) and peripheral SpA (PerSpA) patients initiating etanercept during 2004–2020. Kaplan–Meier plots were used for drug retention comparisons and multivariable Cox regression models for predictors of discontinuation. Long-term disease activity trajectories were identified by latent class growth models using DAS28-ESR or ASDAS-CRP as outcome for RA and AxSpA respectively. We assessed 711 patients (450 RA, 178 AxSpA and 83 PerSpA) with a median (IQR) follow-up of 12 (5–32) months. At 5 years, 22%, 30% and 21% of RA, AxSpA and PerSpA patients, respectively, remained on therapy. Etanercept discontinuation was independent of the diagnosis and was predicted by gender and obesity in both RA and SpA groups. Four disease activity (DA) trajectories were identified from 6th month of treatment in both RA and AxSpA. RA patients in remission-low DA groups (33.7%) were younger, had shorter disease duration, fewer comorbidities and lower baseline disease activity compared to moderate (40.6%) & high DA (25.7%) groups. In AxSpA 74% were in inactive-low DA and they were more often males, non-obese and had lower number of comorbidities compared to higher ASDAS-CRP trajectories. In RA and AxSpA patients, disease activity trajectories revealed heterogeneity of TNFi treatment responses and prognosis. Male gender, lower baseline disease activity and fewer comorbidities, characterize a favourable outcome in terms of disease burden accrual and TNFi survival.

Toward the Next Generation of Precision Medicine

The goal of precision medicine is to develop individualized preventative, predictive, diagnostic, and treatment options that focus on treating a patient with a disease rather than simply curing the disease. The distinction between patient- and disease-focused approaches to healthcare are often contrasted, but both are necessary to develop the next generation of precision medicine. Disease-focused research establishes the standard course of illness, while research into the heterogeneity in onset and treatment responses allows healthcare professionals to tailor treatments to each individual patient. This ambitious objective has evolved over the past two decades and has been influential in treating patients with some types of cancers, cardiovascular diseases, and prenatal screenings. The next generation of precision medicine must integrate genetic, behavioral, and social determinants of health to address individual needs across a broad range of medical conditions. This will require coordinated efforts from multiple stakeholders: researchers, pharmaceutical companies, healthcare providers, and patients.

Comparative Analysis of Tumor Microbiome, Molecular Profile and Immune Cell Abundance by HPV Status in Head and Neck Cancers and Their Impact on Survival

Traditional clinical and molecular prognostic factors offer valuable insight into the heterogeneous natural history and treatment response of head and neck squamous cell carcinoma (HNSCC) yet fail to explain the full spectrum of observed variability. The tumor microenvironment (TME), comprising microbiome and immune cells can impact treatment response and prognosis. We analyzed The Cancer Genome Atlas (TCGA) to evaluate the association of specific microbes and genes in TME with survival and their differential expression in HPV positive (+) and HPV negative (-) HNSCC. HNSCC RNA sequencing (RNAseq) samples from TCGA were processed through the Exogenous sequencing in Tumors and Immune Cells (ExoTIC) pipeline to identify gene expression and microbial presence. HPV status was assessed by detection of papillomaviridae family of microbes. Clinical data from TCGA was extracted to compare overall survival (OS) and control for competing variables using Cox proportional hazards regression. Difference in immune cell abundance was evaluated by Kruskal-Wallis test. All statistical analysis was performed using R. A total of 498 RNAseq samples from TCGA were analyzed. Oral cavity, oropharynx, hypopharynx, and larynx tumors comprised 21.6%, 15%, 1.8%, and 22.2% of specimens, respectively. HPV was detected in 111 patients (22%), most commonly Alpha papillomavirus 9 (90.1%). Of the 5838 enriched microbes, 330 were significantly associated with OS after controlling for tumor stage, smoking, and age. Specifically, the presence of Alpha papillomavirus 9 was associated with significantly improved OS [adjusted HR = 0.60 (95% CI 0.40 - 0.89, p = 0.01)]. Microbial species found in more abundance in HPV- tumors included Citrobacter farmeri, Thermoanaerobacter kivui and Yersinia pestis which are gram negative anaerobes. Genes related to cellular transport and DNA repair were enriched while genes related to proliferation (e.g., SAGE1) were depleted in HPV+ samples. HPV- tumors had a significantly higher number of M0 (p < 0.001) and M2 macrophages (p = 0.035) while HPV+ tumors had more T regulatory cells (p < 0.001) and CD8+ T-cells (p < 0.001). Tumor microenvironment was significantly associated with survival for HNSCC patients, with particular microbes such as Alpha papillomavirus 9 correlating with improved OS. Greater abundance of certain anaerobic microbes was seen in HPV- tumors. These findings suggest TME can be used to predict patient outcomes and potentially guide personalized treatment approaches. We found an abundance of M0 and M2 macrophages in HPV- tumors, which are considered pro-tumorigenic, while anti-tumor M1 macrophages were similar in the two groups. This may help identify mechanism of resistance to immunotherapies and tailor novel immunotherapy combinations in specific patient subgroups. With further prospective research and external validation these findings have the potential to significantly impact the way we treat HNSCC in the future.

Review on Early Ovarian Carcinoma using Radiomics

Ovarian cancer remains one of the deadliest gynecological malignancies in the world, despite major advances in chemotherapy and surgery. This, according to several research, is related to the considerable heterogeneity in treatment response and prognosis. Mostly, computational approaches for assessing tumour heterogeneity have been developed, which employ medical imaging and radio genomes to look at the whole tumour heterogeneity rather than just a single biopsy sample. This tumoral heterogeneity is not taken into consideration by standard imaging utilising CT or MRI, especially in late stages of peritoneal carcinomatosis. As a result, medical imaging has been recommended as a new field in the assessment of tumour heterogeneity, rather than single biopsy sample, to evaluate the entire tumour burden heterogeneity. In medical imaging there are four basic steps involved for an efficient and accurate detection of ovarian cancer at early stage. This review discusses about the detail evaluation on the various four phases involved in Medical imaging. Thus the review brings out a detail evaluation of Medical imaging undertaken at every stage of processing.&#x0D; Bangladesh J Obstet Gynaecol, 2022; Vol. 37(1): 39-46