Current and New Biomarkers for Early Detection, Prognostic Stratification, and Management of Gallbladder Cancer Patients

Gallbladder cancer (GBC) is an aggressive disease that shows evident geographic variation and is characterized by a poor prognosis, mainly due to the late diagnosis and ineffective treatment. Genetic variants associated with GBC susceptibility, including polymorphisms within the toll-like receptors TLR2 and TLR4, the cytochrome P450 1A1 (CYP1A1), and the ATP-binding cassette (ABC) transporter ABCG8 genes, represent promising biomarkers for the stratification of patients at higher risk of GBC; thus, showing potential to prioritize cholecystectomy, particularly considering that early diagnosis is difficult due to the absence of specific signs and symptoms. Similarly, our better understanding of the gallbladder carcinogenic processes has led to identify several cellular and molecular events that may influence patient management, including HER2 aberrations, high tumor mutational burden, microsatellite instability, among others. Despite these reports on interesting and promising markers for risk assessment, diagnosis, and prognosis; there is an unmet need for reliable and validated biomarkers that can improve the management of GBC patients and support clinical decision-making. This review article examines the most potentially significant biomarkers of susceptibility, diagnosis, prognosis, and therapy selection for GBC patients, highlighting the need to find and validate existing and new molecular biomarkers to improve patient outcomes.

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Can Alveolar-Arterial Difference and Lung Ultrasound Help the Clinical Decision Making in Patients with COVID-19?

Diagnostics ◽

10.3390/diagnostics11050761 ◽

2021 ◽

Vol 11 (5) ◽

pp. 761

Author(s):

Gianmarco Secco ◽

Francesco Salinaro ◽

Carlo Bellazzi ◽

Marco La Salvia ◽

Marzia Delorenzo ◽

...

Keyword(s):

Decision Making ◽

Clinical Decision Making ◽

Lung Ultrasound ◽

Signs And Symptoms ◽

Clinical Decision ◽

Arterial Oxygen ◽

Arterial Blood Gas ◽

Arterial Blood ◽

Lung Dysfunction ◽

Close Relationship

Background: COVID-19 is an emerging infectious disease, that is heavily challenging health systems worldwide. Admission Arterial Blood Gas (ABG) and Lung Ultrasound (LUS) can be of great help in clinical decision making, especially during the current pandemic and the consequent overcrowding of the Emergency Department (ED). The aim of the study was to demonstrate the capability of alveolar-to-arterial oxygen difference (AaDO2) in predicting the need for subsequent oxygen support and survival in patients with COVID-19 infection, especially in the presence of baseline normal PaO2/FiO2 ratio (P/F) values. Methods: A cohort of 223 swab-confirmed COVID-19 patients underwent clinical evaluation, blood tests, ABG and LUS in the ED. LUS score was derived from 12 ultrasound lung windows. AaDO2 was derived as AaDO2 = ((FiO2) (Atmospheric pressure − H2O pressure) − (PaCO2/R)) − PaO2. Endpoints were subsequent oxygen support need and survival. Results: A close relationship between AaDO2 and P/F and between AaDO2 and LUS score was observed (R2 = 0.88 and R2 = 0.67, respectively; p < 0.001 for both). In the subgroup of patients with P/F between 300 and 400, 94.7% (n = 107) had high AaDO2 values, and 51.4% (n = 55) received oxygen support, with 2 ICU admissions and 10 deaths. According to ROC analysis, AaDO2 > 39.4 had 83.6% sensitivity and 90.5% specificity (AUC 0.936; p < 0.001) in predicting subsequent oxygen support, whereas a LUS score > 6 showed 89.7% sensitivity and 75.0% specificity (AUC 0.896; p < 0.001). Kaplan–Meier curves showed different mortality in the AaDO2 subgroups (p = 0.0025). Conclusions: LUS and AaDO2 are easy and effective tools, which allow bedside risk stratification in patients with COVID-19, especially when P/F values, signs, and symptoms are not indicative of severe lung dysfunction.

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Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods

10.1101/2021.07.07.21259699 ◽

2021 ◽

Author(s):

Farshad Saberi-Movahed ◽

Mahyar Mohammadifard ◽

Adel Mehrpooya ◽

Mohammad Rezaei-Ravari ◽

Kamal Berahmand ◽

...

Keyword(s):

Feature Selection ◽

Poor Prognosis ◽

Clinical Decision Making ◽

Unmet Need ◽

Clinical Decision ◽

Clinical Indicators ◽

Arterial Blood Gas ◽

Clinical Biomarkers ◽

Arterial Blood ◽

Global Pandemic

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients' characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Ma- trix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O2 Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases.

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Management of Cardiac Toxicity Induced by Chemotherapy

Journal of Clinical Medicine ◽

10.3390/jcm9092885 ◽

2020 ◽

Vol 9 (9) ◽

pp. 2885 ◽

Cited By ~ 1

Author(s):

Dario Trapani ◽

Paola Zagami ◽

Eleonora Nicolò ◽

Gabriella Pravettoni ◽

Giuseppe Curigliano

Keyword(s):

Clinical Decision Making ◽

Current Knowledge ◽

Early Recognition ◽

Clinical Decision ◽

Cancer Treatments ◽

Drug Induced ◽

Medical Interventions ◽

Clinical Scenarios ◽

New Biomarkers ◽

Chemotherapy Agents

Cardiotoxicity encompasses a spectrum of adverse cardiological effects experienced by cancer patients during and after receiving antineoplastic treatments. The intersection of cancer care with the management of the multiple comorbid non-communicable diseases carried by patients or related to cancer treatments motivates the need for an integrated and multidisciplinary approach to therapeutic clinical decision-making. This present review aimed to provide a perspective and an update of the current pharmacotherapy approaches for the prevention and management of cardiotoxicity from antiblastic chemotherapy; as such, it addresses myocardial, vascular, and arrhythmic disorders associated to chemotherapy, by navigating the current knowledge and clinical indications in support of the medical interventions. Clinical scenarios of pharmacological interventions take place with patients receiving anthracycline and, by extrapolation, other agents with cardiotoxic potentials and non-chemotherapy agents, including various small molecules and immunotherapy agents. Analysis of these scenarios aims to provide practical evidence-based guidance for the management of drug-induced cardiac dysfunctions. The possible role of new biomarkers for the early recognition of cardiotoxicity is mentioned across the clinical studies, with reference to the pharmacological biomarker-driven interventions delivered. To best inform survivorship care, the management and context of cardio-oncology services are discussed within the broader network of providers and settings of care.

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A comparison of patients' and physicians' expectations regarding precision oncology tests.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.1568 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. 1568-1568

Author(s):

Navdeep Dehar ◽

Tasnima Abedin ◽

Patricia A. Tang ◽

D. Gwyn Bebb ◽

Winson Y. Cheung

Keyword(s):

Decision Making ◽

Genetic Testing ◽

Cancer Biology ◽

Clinical Decision Making ◽

Clinical Decision ◽

Survey Study ◽

Precision Oncology ◽

Diagnosis And Prognosis ◽

Genetic Test Results ◽

Survey Responses

1568 Background: With the increasing number and frequency of biomarker and genetic tests that are offered to patients with cancer, it is important to ensure that they fully understand the implications of these tests. In this survey study, we aimed to compare the attitudes and expectations of patients and cancer physicians about the role of biomarker and genetic testing in clinical decision-making. Methods: Two separate, complimentary, self-administered questionnaires for cancer patients and their physicians, respectively, were collected in Calgary, Alberta, Canada. Survey responses from patients were subsequently matched with those of their corresponding oncologists to form patient–oncologist dyads. We determined the concordance rates between responses of patients and those of their oncologists. Results: A total of 113 patients and 15 physicians participated in the study from July to September 2019. Patients demonstrated good understanding of general cancer biology (79%) and diagnostic processes (91%) associated with precision oncology. About 70% patients were willing to undergo minor procedures, and participate in research involving biomarker or genetic testing; however, this was over-estimated by their physicians in 82% of cases. Many patients felt that their tumor should be tested to guide treatment (70%) and were not bothered by potential delays in treatment due to testing (23%). These views from patients were largely shared by their oncologists (concordance 64%). While only 28% patients thought that they had enough knowledge to make informed decisions, majority (68%) said that they needed more information. Importantly, knowledge and expectations regarding the applications of biomarker or genetic test results on actual diagnosis and prognosis were grossly discrepant between patients and their oncologists (concordance 26% and 36%, respectively). Conclusions: Patients and cancer physicians tend to be aware of the advances in precision oncology and are willing to participate in biomarker and genetic testing and research. However, they do not consistently agree about the roles and applications of these tests, which may result in misplaced expectations. Strategies to improve education and communication are needed to align these expectations and improve the quality of clinical decision-making.

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Cytogenetic as an Important Tool for Diagnosis and Prognosis for Patients with Hypocellular Primary Myelodysplastic Syndrome

BioMed Research International ◽

10.1155/2014/542395 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10 ◽

Cited By ~ 4

Author(s):

Daiane Corrêa de Souza ◽

Cecília de Souza Fernandez ◽

Adriana Camargo ◽

Alexandre Gustavo Apa ◽

Elaine Sobral da Costa ◽

...

Keyword(s):

Clinical Decision Making ◽

Chromosomal Abnormalities ◽

Critical Role ◽

Clinical Decision ◽

High Association ◽

Score System ◽

Diagnosis And Prognosis ◽

Group 2 ◽

Group 1

We analyzed cytogenetically 105 patients with hypocellular primary MDS and their clinical implications. The main chromosomal abnormalities found were del(5q)/−5, del(6q)/+6, del(7q)/−7, del(11q), and del(17p). Pediatric patients had a higher frequency of abnormal karyotypes compared with adult patients (P< 0,05). From our patients, 18% showed evolution of the disease. The chromosomal abnormalities presented in the diagnosis of patients who evolved to AML included numerical (−7, +8) and structural del(6q), del(7q), i(7q), t(7;9), i(9q), and del(11q) abnormalities and complex karyotypes. Although the frequency of evolution from hypocellular MDS to AML is low, our results suggest that some chromosomal alterations may play a critical role during this process. We applied the IPSS in our patients because this score system has been proved to be useful for predicting evolution of disease. When we considered the patients according to group 1 (intermediate-1) and group 2 (intermediate-2 and high risk), we showed that group 2 had a high association with respect to the frequency of abnormal karyotypes (P< 0,0001), evolution of disease (P< 0,0001), and mortality (P< 0,001). In fact, the cytogenetic analysis for patients with hypocellular primary MDS is an important tool for diagnosis, prognosis, in clinical decision-making and in follow-up.

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Translating the Science of Patient Reported Outcomes into Practice: Meaningfulness of HM-PRO Scores in Patients with Hematological Malignancies

Blood ◽

10.1182/blood-2018-99-117180 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4860-4860 ◽

Cited By ~ 3

Author(s):

Pushpendra Goswami ◽

Esther Natalie Oliva ◽

Tatyana Ionova ◽

Sam Salek

Keyword(s):

Hodgkin Lymphoma ◽

Myeloid Leukemia ◽

Clinical Decision Making ◽

Signs And Symptoms ◽

Clinical Decision ◽

Cross Sectional ◽

Non Hodgkin Lymphoma ◽

Patient Reported ◽

The Mean ◽

The Impact

Abstract Introduction: Patient-reported outcome (PRO) measures not only have been widely used in clinical research but also increasingly employed in daily clinical practice to understand the health outcomes of medical interventions. A novel hematological malignancy (HM) specific PRO tool, HM-PRO, has been recently developed for use in daily clinical practice. The HM-PRO is a composite measure consisting of two scales: Part A - measuring the 'impact on patients' quality of life (QoL); and Part B-measuring the effect of 'signs and symptoms' experienced by the patients. Both scales have linear scoring system ranging from 0 to 100, with higher scores representing greater impact on QoL and symptom burden. The assessment of the "meaningfulness" of HM-PRO scores is essential if clinicians are to be able to use the instrument to understand patient health outcomes to aid their clinical decision-making and encourage better patient engagement. One way of enhancing the clinical utility of scores on multi-item questionnaires is by investigating the importance (to patients and clinicians) of cross-sectional differences by anchoring those differences and changes to clinically familiar events that are related to patient well-being. The aims of the present study were to determine the relationship between the HM-PRO scores and a Global Question (GQ) measuring the impact on a patient's life from patients' perspective and to identify bands of HM-PRO scores equivalent to each GQ descriptor, reflecting patients' global rating of PROs. Methods: In this multicenter cross-sectional study, 905 patients: male 486; mean age 64.3 (±12.4, years; mean time since diagnosis 4.6 (±5.2) years; with different HM's ( acute lymphoblastic leukemia n=29, acute myeloid leukemia n=67, aggressive non Hodgkin lymphoma n=54, chronic lymphocytic leukemia n=64, chronic myeloid leukemia n=45, Hodgkin lymphoma n=37, indolent non Hodgkin lymphoma n=41, myelodysplastic syndrome n=158, multiple myeloma n=296, and myeloproliferative neoplasm n=114); in different disease states (stable-399, remission-277, and progressing - 229) were recruited from seven secondary hospitals and five patient organizations in the UK. All patients were asked to complete the HM-PRO and answer the global question as an anchor. Anchor-based differences were determined cross-sectionally (differences between clinically-defined groups at one time point) to determine clinically important differences in scores. The data analysis was carried out using IBM SPSS 23, a statistical software. Results: The mean HM-PRO score for Part A was 31.7 (±21.6) with median of 28.3 (IQR 13.6-46.6), for Part B was 20.9 (±14.2) with median of 17.6 (IQR 8.8 - 29.4), and the mean GQ score was 3.2 (±1.19) with range 1-5. The mean, mode, and median of the GQ scores for each HM-PRO score for both scales of HM-PRO were used to devise the bands (Figure 1) and intra-class correlation coefficient (ICC) was calculated for level of agreement. The set of scores proposed for adoption included: for Part A HM-PRO scores 0-7 = 'no impact' on patients' QoL (GQ=1, n=64), scores 8-25 = 'a small impact' on patients' QoL (GQ=2, n=133), scores 26-41 = 'moderate impact' on patients' QoL (GQ=3, n=97), scores 42-74 = 'very large impact' on patients' QoL (GQ=4, n=111), and scores 75-100 = 'extremely large impact' on patients' QoL (GQ=5, n=18), with ICC =0.80 (95% CI-0.77 - 0.83); for Part B HM-PRO scores 0-3 = 'no effect' of signs and symptoms on patient's life (GQ=1, n=56), scores 4-16 = 'a small effect' of signs and symptoms on patient's life (GQ=2, n=133), scores 17-29 = 'a moderate effect' of signs and symptoms on patient's life (GQ=3, n=122), scores 30-65 = 'very large effect' of signs and symptoms on patient's life (GQ=4, n=104), and scores 66-100 = 'extremely large effect' of signs and symptoms on patient's life (GQ=5, n=3), with ICC =0.75 (95% CI- 0.71-0.78), respectively (Table 1). Conclusion: This study employed the anchor-based approach for devising a set of score banding for both Part A and Part B of HM-PRO. The proposed bands (Part A=0-7, 8-25, 26-41, 42-74, 75-100; Part B=0-3, 4-16, 17-29, 30-65, 66-100) had the highest agreement and number of patients in the individual bands. The proposed bands could be applied independent of gender and different age groups. The findings of this study will help the clinician and the care team to interpret the HM-PRO scores to aid their clinical decision-making process in daily routine practice. Disclosures Oliva: Sanofi: Consultancy, Speakers Bureau; Celgene: Consultancy, Other: Royalties, Speakers Bureau; La Jolla: Consultancy; Amgen: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau. Ionova:Takeda: Research Funding; BMS: Research Funding.

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Nurses' Knowledge of Signs and Symptoms of Anxiety and Agitation

10.28971/532015dc75 ◽

2015 ◽

Author(s):

Cindy DiSano

Keyword(s):

Rhode Island ◽

Health Care Professionals ◽

Clinical Decision Making ◽

Signs And Symptoms ◽

Clinical Decision ◽

The United States ◽

National Standards ◽

Inpatient Setting ◽

Study Approach ◽

Nurses Knowledge

<p>The diagnosis of mental illness is becoming more prevalent in the United States. With the increased identification, it is imperative that health care professionals are astute in identifying mental health conditions and behaviors associated with those conditions. The most common use of pro re nata (PRN) or “as needed” psychoactive medications in the inpatient psychiatric setting is for the reduction of behaviors associated with anxiety, agitation, and aggression. The administration of PRN medication rests solely on the nursing staff and their ability to use autonomous clinical decision-making to distinguish between different behaviors associated with those conditions prior to the administration of PRN medication. For the past 30 years, research has recognized the lack of national standards, assessment criteria, and ethical practices when administrating PRN medications in the acute inpatient setting. The purpose of this study was to identify nurses’ knowledge of signs and symptoms of anxiety or agitation in the acute care setting. The model used to guide this research is the Synergy Model of Patient Care. The design for this research study was a descriptive design using a case study approach. This study was conducted at a nonprofit, general medical-surgical community hospital in Rhode Island specializing in rehabilitation and psychiatric services. The target sample consisted of all registered nurses working on three study units. Two case studies, each portraying a patient experiencing symptoms or behaviors of anxiety and agitation were used to measure nurses’ knowledge of signs and symptoms of anxiety and agitation. A total of 17 RNs (N=17) participated in this research project. This research implied that there were gaps in clinical knowledge and variations in practice when nurses were asked to recognize symptoms of anxiety or behaviors associated with agitation. </p>

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ecTMB: a robust method to estimate and classify tumor mutational burden

10.1101/602060 ◽

2019 ◽

Author(s):

Lijing Yao ◽

Yao Fu ◽

Marghoob Mohiyuddin ◽

Hugo YK Lam

Keyword(s):

Somatic Mutations ◽

Clinical Decision Making ◽

Patient Survival ◽

Clinical Decision ◽

Statistical Framework ◽

Mutational Burden ◽

Mutation Model ◽

Tumor Mutational Burden ◽

Multiple Challenges

AbstractTumor Mutational Burden (TMB) is a measure of the abundance of somatic mutations in a tumor, which has been shown to be an emerging biomarker for both anti-PD-(L)1 treatment and prognosis. Nevertheless, multiple challenges still hinder the adoption of TMB for clinical decision-making. The key challenges are the inconsistency of TMB measurement among assays and a lack of meaningful threshold for TMB classification. We describe a powerful and flexible statistical framework for estimation and classification of TMB (ecTMB). ecTMB uses an explicit background mutation model to predict TMB robustly and consistently. In addition to the two known TMB subtypes, TMB-high and TMB-low, we discovered a novel TMB subtype, named TMB-extreme, which was significantly associated with patient survival outcome. This discovery enabled ecTMB to classify samples to biologically and clinically relevant subtypes defined by TMB.

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Current Molecular Markers of Melanoma and Treatment Targets

International Journal of Molecular Sciences ◽

10.3390/ijms21103535 ◽

2020 ◽

Vol 21 (10) ◽

pp. 3535 ◽

Cited By ~ 2

Author(s):

Kevin Yang ◽

Allen S.W. Oak ◽

Radomir M. Slominski ◽

Anna A. Brożyna ◽

Andrzej T. Slominski

Keyword(s):

Clinical Decision Making ◽

Clinical Decision ◽

Genetic Alterations ◽

Diagnostic Tools ◽

Genetic Mutations ◽

Molecular Alterations ◽

Diagnosis And Prognosis ◽

Appropriate Treatment ◽

Histopathologic Diagnosis ◽

Malignant Lesions

Melanoma is a deadly skin cancer that becomes especially difficult to treat after it metastasizes. Timely identification of melanoma is critical for effective therapy, but histopathologic diagnosis can frequently pose a significant challenge to this goal. Therefore, auxiliary diagnostic tools are imperative to facilitating prompt recognition of malignant lesions. Melanoma develops as result of a number of genetic mutations, with UV radiation often acting as a mutagenic risk factor. Novel methods of genetic testing have improved detection of these molecular alterations, which subsequently revealed important information for diagnosis and prognosis. Rapid detection of genetic alterations is also significant for choosing appropriate treatment and developing targeted therapies for melanoma. This review will delve into the understanding of various mutations and the implications they may pose for clinical decision making.

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Predicting Clinical Outcomes Using Molecular Biomarkers

Biomarkers in Cancer ◽

10.4137/bic.s33380 ◽

2016 ◽

Vol 8 ◽

pp. BIC.S33380 ◽

Cited By ~ 43

Author(s):

Harry B. Burke

Keyword(s):

Decision Making ◽

Clinical Outcomes ◽

Clinical Decision Making ◽

Clinical Care ◽

Clinical Decision ◽

Molecular Biomarkers ◽

The Past ◽

Diagnosis And Prognosis ◽

Molecular Therapies ◽

Physician Patient

Over the past 20 years, there has been an exponential increase in the number of biomarkers. At the last count, there were 768,259 papers indexed in PubMed.gov directly related to biomarkers. Although many of these papers claim to report clinically useful molecular biomarkers, embarrassingly few are currently in clinical use. It is suggested that a failure to properly understand, clinically assess, and utilize molecular biomarkers has prevented their widespread adoption in treatment, in comparative benefit analyses, and their integration into individualized patient outcome predictions for clinical decision-making and therapy. A straightforward, general approach to understanding how to predict clinical outcomes using risk, diagnostic, and prognostic molecular biomarkers is presented. In the future, molecular biomarkers will drive advances in risk, diagnosis, and prognosis, they will be the targets of powerful molecular therapies, and they will individualize and optimize therapy. Furthermore, clinical predictions based on molecular biomarkers will be displayed on the clinician's screen during the physician–patient interaction, they will be an integral part of physician–patient-shared decision-making, and they will improve clinical care and patient outcomes.

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