Treatment Response
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2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 154-154
Joy X. Jarnagin ◽  
Islam Baiev ◽  
Emily E. Van Seventer ◽  
Yojan Shah ◽  
Amirkasra Mojtahed ◽  

154 Background: PROs assessing quality of life (QOL) and symptoms at a single timepoint frequently correlate with clinical outcomes in patients with cancer, yet efforts to understand how longitudinal changes in PROs can predict for treatment outcomes are lacking. In practice, oncologists often use changes in serum TMs (CEA and CA19-9) to monitor patients with GI cancer, and thus we sought to examine associations of 1-month changes in PROs and TMs with treatment response and survival outcomes among patients with advanced GI cancer. Methods: We prospectively enrolled patients with metastatic GI cancer prior to initiating chemotherapy at Massachusetts General Hospital from 5/2019-12/2020. At baseline (start of treatment) and 1-month later, we collected PROs (QOL [Functional Assessment of Cancer Therapy General {FACT-G}], physical symptoms [Edmonton Symptom Assessment System {ESAS}], and psychological symptoms [Patient Health Questionnaire-4 {PHQ-4}]) and TMs. We used regression models to examine associations of 1-month changes in PROs and TMs with treatment response (clinical benefit [defined as decreased or stable tumor burden] or progressive disease at the time of first scan) and survival outcomes (progression-free survival [PFS] and overall survival [OS]), adjusted for baseline values of each respective variable. Results: We enrolled 159 of 191 patients approached (83.2% enrollment); 134 had 1-month follow-up data (median age = 64 years [range: 28 to 84 years], 64.2% male, 46.3% pancreaticobiliary cancer). For treatment response, 63.4% had clinical benefit and 36.6% had progressive disease at the time of first scan (mean time to first scan = 2.01 months). Changes in PROs (ESAS-Total: OR = 0.97, p = 0.022; ESAS-Physical: OR = 0.96, p = 0.027; PHQ-4 depression: OR = 0.67, p = 0.014; FACT-G: OR = 1.07, p = 0.001), but not TMs (CEA: OR = 1.00, p = 0.836 and CA19-9: OR = 1.00, p = 0.796), were associated with clinical benefit at the time of first scan. Changes in ESAS-Total (HR = 1.03, p = 0.004), ESAS-Physical (HR = 1.03, p = 0.021), PHQ-4 depression (HR = 1.22, p = 0.042), FACT-G (HR = 0.97, p = 0.003), and CEA (HR = 1.00, p = 0.001) were predictors of PFS. Changes in ESAS-Total (HR = 1.03, p = 0.006) and ESAS-Physical (HR = 1.04, p = 0.015) were predictors of OS, but 1-month changes in TMs (CEA: HR = 1.00, p = 0.377 and CA19-9: HR = 1.00, p = 0.367) did not significantly predict for OS. Conclusions: We found that 1-month changes in PROs can predict for treatment response and survival outcomes in patients with advanced GI cancers. Notably, 1-month changes in CEA only correlated with PFS, while changes in CA19-9 did not significantly predict treatment response or survival outcomes. These findings highlight the potential for early changes in PROs to predict treatment outcomes while underscoring the need to monitor and address PROs in patients with advanced cancer. Clinical trial information: NCT04776837.

Cancers ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 4717
Sandra Wagner ◽  
Nicola T. Beger ◽  
Stephanie Matschos ◽  
Antonia Szymanski ◽  
Randy Przybylla ◽  

The prognosis of metastatic colorectal cancer (CRC) remains poor. Patients and physicians are in need of individual therapies and precise response predictions. We investigated the predictive capacity of primary tumour material for treatment response of metastases. Mutational landscapes of primary tumours and corresponding metastases of 10 CRC patients were compared. Cell line characteristics and chemosensitivity were investigated pairwise for primary and metastatic tumours of four patients. PDX models of one patient were treated in vivo for proof of concept. Driver mutations did not differ between primaries and metastases, while the latter accumulated additional mutations. In vitro chemosensitivity testing revealed no differences for responses to 5-FU and oxaliplatin between primary and metastatic cell lines. However, irinotecan response differed significantly: the majority of metastases-derived cell lines was less sensitive to irinotecan than their matching primary counterpart. Therapy recommendations based on these findings were compared to clinical treatment response and mostly in line with the predicted outcome. Therefore, primary tumour cell models seem to be a good tool for drug response testing and conclusion drawing for later metastases. With further data from tumour-derived cell models, such predictions could improve clinical treatment decisions, both recommending likely effective therapeutic options while excluding ineffective treatments.

2021 ◽  
Vol 6 (1) ◽  
Nicholas R. Rydzewski ◽  
Erik Peterson ◽  
Joshua M. Lang ◽  
Menggang Yu ◽  
S. Laura Chang ◽  

AbstractWe are now in an era of molecular medicine, where specific DNA alterations can be used to identify patients who will respond to specific drugs. However, there are only a handful of clinically used predictive biomarkers in oncology. Herein, we describe an approach utilizing in vitro DNA and RNA sequencing and drug response data to create TreAtment Response Generalized Elastic-neT Signatures (TARGETS). We trained TARGETS drug response models using Elastic-Net regression in the publicly available Genomics of Drug Sensitivity in Cancer (GDSC) database. Models were then validated on additional in-vitro data from the Cancer Cell Line Encyclopedia (CCLE), and on clinical samples from The Cancer Genome Atlas (TCGA) and Stand Up to Cancer/Prostate Cancer Foundation West Coast Prostate Cancer Dream Team (WCDT). First, we demonstrated that all TARGETS models successfully predicted treatment response in the separate in-vitro CCLE treatment response dataset. Next, we evaluated all FDA-approved biomarker-based cancer drug indications in TCGA and demonstrated that TARGETS predictions were concordant with established clinical indications. Finally, we performed independent clinical validation in the WCDT and found that the TARGETS AR signaling inhibitors (ARSI) signature successfully predicted clinical treatment response in metastatic castration-resistant prostate cancer with a statistically significant interaction between the TARGETS score and PSA response (p = 0.0252). TARGETS represents a pan-cancer, platform-independent approach to predict response to oncologic therapies and could be used as a tool to better select patients for existing therapies as well as identify new indications for testing in prospective clinical trials.

Amina Alobaidi ◽  
Abdulghani Alsamarai ◽  
Mohamed Almoustafa Alsamarai

: Asthma is a chronic disease with abnormal inflammatory and immunological responses. The disease initiated by antigens in subjects with genetic susceptibility. However, environmental factors play a role in the initiation and exacerbation of asthma attack. Asthma is T helper 2 (Th2)-cell-mediated disease. Recent studies indicated that asthma is not a single disease entity, but it is with multiple phenotypes and endotypes. The pathophysiological changes in asthma included a series of subsequent continuous vicious circle of cellular activation contributed to induction of chemokines and cytokines that potentiate inflammation. The heterogeneity of asthma influenced the treatment response. The asthma pathogenesis driven by varied set of cells such as eosinophils, basophils, neutrophils, mast cells, macrophages, epithelial cells and T cells. In this review the role of T cells, macrophage, and epithelial cells are discussed.

Jose J.G. Marin ◽  
Marta R. Romero ◽  
Elisa Herraez ◽  
Maitane Asensio ◽  
Sara Ortiz-Rivero ◽  

AbstractHepatocellular carcinoma (HCC) is a malignancy with poor prognosis when diagnosed at advanced stages in which curative treatments are no longer applicable. A small group of these patients may still benefit from transarterial chemoembolization. The only therapeutic option for most patients with advanced HCC is systemic pharmacological treatments based on tyrosine kinase inhibitors (TKIs) and immunotherapy. Available drugs only slightly increase survival, as tumor cells possess additive and synergistic mechanisms of pharmacoresistance (MPRs) prior to or enhanced during treatment. Understanding the molecular basis of MPRs is crucial to elucidate the genetic signature underlying HCC resistome. This will permit the selection of biomarkers to predict drug treatment response and identify tumor weaknesses in a personalized and dynamic way. In this article, we have reviewed the role of MPRs in current first-line drugs and the combinations of immunotherapeutic agents with novel TKIs being tested in the treatment of advanced HCC.

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Bijun Wen ◽  
Daniella Brals ◽  
Celine Bourdon ◽  
Lauren Erdman ◽  
Moses Ngari ◽  

Abstract Background Despite adherence to WHO guidelines, inpatient mortality among sick children admitted to hospital with complicated severe acute malnutrition (SAM) remains unacceptably high. Several studies have examined risk factors present at admission for mortality. However, risks may evolve during admission with medical and nutritional treatment or deterioration. Currently, no specific guidance exists for assessing daily treatment response. This study aimed to determine the prognostic value of monitoring clinical signs on a daily basis for assessing mortality risk during hospitalization in children with SAM. Methods This is a secondary analysis of data from a randomized trial (NCT02246296) among 843 hospitalized children with SAM. Daily clinical signs were prospectively collected during ward rounds. Multivariable extended Cox regression using backward feature selection was performed to identify daily clinical warning signs (CWS) associated with time to death within the first 21 days of hospitalization. Predictive models were subsequently developed, and their prognostic performance evaluated using Harrell’s concordance index (C-index) and time-dependent area under the curve (tAUC). Results Inpatient case fatality ratio was 16.3% (n=127). The presence of the following CWS during daily assessment were found to be independent predictors of inpatient mortality: symptomatic hypoglycemia, reduced consciousness, chest indrawing, not able to complete feeds, nutritional edema, diarrhea, and fever. Daily risk scores computed using these 7 CWS together with MUAC<10.5cm at admission as additional CWS predict survival outcome of children with SAM with a C-index of 0.81 (95% CI 0.77–0.86). Moreover, counting signs among the top 5 CWS (reduced consciousness, symptomatic hypoglycemia, chest indrawing, not able to complete foods, and MUAC<10.5cm) provided a simpler tool with similar prognostic performance (C-index of 0.79; 95% CI 0.74–0.84). Having 1 or 2 of these CWS on any day during hospitalization was associated with a 3 or 11-fold increased mortality risk compared with no signs, respectively. Conclusions This study provides evidence for structured monitoring of daily CWS as recommended clinical practice as it improves prediction of inpatient mortality among sick children with complicated SAM. We propose a simple counting-tool to guide healthcare workers to assess treatment response for these children. Trial registration NCT02246296

2021 ◽  
Vol 1 ◽  
pp. 46
Renita Lourdhurajan ◽  
Subashini Selvadurairaj

The approach to managing acne scars is unique to every dermatologist. This depends on the skin type of his/her clientele, the tools, techniques and devices available and/or used, and the protocols developed based on his/her experience with treating acne scars, developed over a period of time. Herein, we share our algorithmic treatment approach to acne scars, which allows for a consultative decision-making together with the patient, while offering adequate flexibility to modify the plan based on treatment response. Eventually, a customized and comprehensive system works best, and a partnership approach signified by a robust self-care home plan, helps accelerate the scar revision process.

2021 ◽  
Vol 237 ◽  
pp. 153-165
Urvakhsh Meherwan Mehta ◽  
Ferose Azeez Ibrahim ◽  
Manu S. Sharma ◽  
Ganesan Venkatasubramanian ◽  
Jagadisha Thirthalli ◽  

2021 ◽  
Mu-Hong Chen ◽  
Wei-Chen Lin ◽  
Cheng-Ta Li ◽  
Shih-Jen Tsai ◽  
Hui-Ju Wu ◽  

Abstract Introduction Pretreatment neurocognitive function may predict the treatment response to low-dose ketamine infusion in patients with treatment-resistant depression (TRD). However, the association between working memory function at baseline and the antidepressant efficacy of ketamine infusion remains unclear. Methods A total of 71 patients with TRD were randomized to one of three treatment groups: 0.5 mg/kg ketamine, 0.2 mg/kg ketamine, or normal saline. Depressive symptoms were measured using the 17-item Hamilton Depression Rating Scale (HDRS) at baseline and after treatment. Cognitive function was evaluated using working memory and go-no-go tasks at baseline. Results A generalized linear model with adjustments for demographic characteristics, treatment groups, and total HDRS scores at baseline revealed only a significant effect of working memory function (correct responses and omissions) on the changes in depressive symptoms measured by HDRS at baseline (F=12.862, p<0.05). Correlation analysis further showed a negative relationship (r=0.519, p=0.027) between pretreatment working memory function and changes in HDRS scores in the 0.5 mg/kg ketamine group. Discussion An inverse relationship between pretreatment working memory function and treatment response to ketamine infusion may confirm that low-dose ketamine infusion is beneficial and should be reserved for patients with TRD.

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1681
Cristina Ferrari ◽  
Giulia Santo ◽  
Nunzio Merenda ◽  
Alessia Branca ◽  
Paolo Mammucci ◽  

Introduction: The aim of this study was to investigate whether [18F]FDG PET/CT-derived semi-quantitative parameters can predict immunotherapy treatment response in non-small cell lung cancer (NSCLC) patients. Secondly, immune-related adverse events (irAEs) and lymphoid cell-rich organs activation were evaluated. Materials and Methods: Twenty-eight patients who underwent [18F]FDG PET/CT scans before and at first restaging therapy with immuno-checkpoint inhibitors (ICIs) were retrospectively analyzed. PET-based semi-quantitative parameters extracted from both scans were respectively: SUVmax and SUVpeak of the target lesion, whole-body metabolic tumor volume (MTVWB), and whole-body total lesion glycolysis (TLGWB), as well as their interval changes (ΔSUVmaxTL, ΔSUVpeakTL, ΔMTVWB, ΔTLGWB). These PET-derived parameters were correlated to controlled disease (CD) assessed by RECIST 1.1. IrAEs, if present, were also described and correlated with clinical benefit (CB). SUVmax of the spleen and bone marrow at restaging scans were also correlated to CB. Results: The CD was achieved in 54% of patients. Out of 28 eligible patients, 13 (46%) experienced progressive disease (PD), 7 showed SD, 7 had PR, and only in one patient CR was achieved. ΔSUVmaxTL (p = 0.002) and ΔSUVpeakTL (p < 0.001) as well as ΔMTVWB (p < 0.001) and ΔTLGWB (p < 0.005) were significantly associated with PD vs. non-PD. IrAEs and lymphoid cell-rich organs activation did not correlate with CB. Conclusions: [18F]FDG PET/CT by using interval changes of PET-derived semi-quantitative parameters could represent a reliable tool in immunotherapy treatment response evaluation in NSCLC patients.

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