scholarly journals Bayesian Framework to Augment Tumor Board Decision Making

2021 ◽  
pp. 508-517
Author(s):  
Stefano Pasetto ◽  
Robert A. Gatenby ◽  
Heiko Enderling
Keyword(s):  
Specific Treatment ◽  
Tumor Board ◽  
Patient Specific ◽  
Published Data ◽  
Specific Response ◽  
Mathematical Framework ◽  
Mathematical Tool ◽  
Bayesian Decision ◽  
Tumor Boards ◽  
Board Decision Making

PURPOSE Ideally, specific treatment for a cancer patient is decided by a multidisciplinary tumor board, integrating prior clinical experience, published data, and patient-specific factors to develop a consensus on an optimal therapeutic strategy. However, many oncologists lack access to a tumor board, and many patients have incomplete data descriptions so that tumor boards must act on imprecise criteria. We propose these limitations to be addressed through a flexible but rigorous mathematical tool that can define the probability of success of given therapies and be made readily available to the oncology community. METHODS We present a Bayesian approach to tumor forecasting using a multimodel framework to predict patient-specific response to different targeted therapies even when historical data are incomplete. RESULTS We demonstrate that the Bayesian decision theory's integrative power permits the simultaneous assessment of a range of therapeutic options. CONCLUSION This methodology proposed, built upon a robust and well-established mathematical framework, can play a crucial role in supporting patient-specific clinical decisions by individual oncologists and multispecialty tumor boards.

Comparison of treatment plans feasible through AI enabled multidisciplinary online tumor board solution versus NCCN-based clinical decision support system (CDSS).

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 816-816
Author(s):  
Bhawna Sirohi ◽  
Sushil Beriwal ◽  
C. S. Pramesh ◽  
Supriya Chopra ◽  
Mahesh Goel ◽  
...  
Keyword(s):  
Large Scale ◽  
Treatment Plan ◽  
Specific Treatment ◽  
Treatment Decisions ◽  
Added Value ◽  
Tumor Board ◽  
Patient Specific ◽  
Clinical Scenarios ◽  
Tumor Boards ◽  
Treatment Plans

816 Background: Multidisciplinary tumor boards at Academic Medical Centers (AMC) maximize cancer outcomes. Guidelines based CDSS are alternatives to determine care pathways. Since 2015, 300 AMC cancer experts in USA and India use an AI enabled online tumor board solution, “NAVYA,” to scale low cost access to multidisciplinary expertise, on 1-2 minutes of expert time per decision (ASCO 2017). Methods: GI patients who used NAVYA between 5/1/15-8/31/19 were analyzed. Actionable treatment plans generated by NAVYA were compared to NCCN. Actionable treatment plans include chemotherapy protocols (doses, frequencies), radiation protocols (sites, fractions), etc. Inactionable specialty level decisions (CT-RT vs. surgery) lack specificity. Results: 1302 patients (4638 treatment decisions) were analyzed: 61% (794) male, 80% between age 45 to 75, mostly with Colon, Pancreas, Gallbladder, Rectum, or Stomach cancer; 49.7% non-metastatic. Cohort was comparable to GLOBOCAN estimates. In 82.2% (3812/4638) decisions, NAVYA added value beyond NCCN. First, in 4.5% (212/4638), NAVYA recommended a patient-specific treatment plan that was not part of NCCN. Second, in 3.2% (148/4638), NAVYA recommended treatments plan for clinical scenarios not covered by NCCN, (for eg. 3rd line therapies). Third, in 74.5% (3452/4638), NAVYA used patient specific criteria including resource constraints and patient preference to choose a treatment plan amongst the multiple pathways provided by NCCN and added actionable treatment details. Conclusions: Guideline based CDSS are insufficient to make the vast majority of actionable treatment decisions. Scaling rapid access to multidisciplinary experts is critical. Leapfrogging existing guidelines based CDSS, NAVYA online tumor board makes actionable expert treatment plans possible at a large scale.

INNV-16. CNS-TAP TOOL RECOMMENDATIONS OF TARGETED ANTI-CANCER AGENTS COMPARED TO THOSE SELECTED BY A MULTIDISCIPLINARY TUMOR BOARD IN A MOLECULARLY-DRIVEN DIPG CLINICAL TRIAL (PNOC003)

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi108-vi108
Author(s):  
Holly Roberts ◽  
Karthik Ravi ◽  
Allison Schepers ◽  
Bernard Marini ◽  
Cassie Kline ◽  
...  
Keyword(s):  
Anticancer Agents ◽  
Treatment Plan ◽  
Study Participant ◽  
Targeted Treatment ◽  
Tumor Board ◽  
Patient Specific ◽  
Genomic Profiling ◽  
Genetic Sequencing ◽  
Tumor Boards ◽  
Multidisciplinary Tumor Board

Abstract Genetic sequencing of diffuse intrinsic pontine gliomas (DIPG) has revealed genomic heterogeneity, sparking an interest in individualized and targeted treatment options for this particularly devastating disease. A feasibility study, PNOC003: Molecular Profiling for Individualized Treatment Plan for DIPG (NCT02274987), was completed within the Pacific Pediatric Neuro-Oncology Consortium. In this study, a multidisciplinary tumor board reviewed detailed molecular and genomic profiling of each participant’s tumor and made molecularly-targeted treatment recommendations. Separately, our team developed the Central Nervous System Targeted Agent Prediction (CNS-TAP) tool, which combines pre-clinical, clinical, and CNS penetration data with patient-specific genomic information to derive numeric scores for targeted anticancer agents, aimed to objectively evaluate these therapies for use in patients with CNS tumors. We hypothesized that highly-scored agents within CNS-TAP would overlap with the agents recommended by the tumor board in PNOC003. For each study participant, we used the genomic profiling report to identify actionable alterations and incorporated these data into CNS-TAP to identify the highest-scoring agents. We compared high-scoring agents within CNS-TAP with recommendations from the tumor board for each of the enrolled 28 participants. Overall, 93% of patients (26/28) had at least one agent recommended by both the tumor board and CNS-TAP. Additionally, 38% of all agents (36/95) recommended by the tumor board were also selected by CNS-TAP. We identified factors that likely contributed to the differences in therapy recommendations between these two methods: CNS-TAP requires additional clinician input to account for drug-drug interactions, includes only classically-defined anticancer agents, and cannot easily be updated in real-time as new data emerge. However, CNS-TAP provides an objective evaluation of targeted therapies, whereas tumor boards are inherently subjective. A prospective study incorporating both CNS-TAP and a molecular tumor board for targeted therapy selection in high-grade glioma is currently ongoing to further compare and objectively evaluate these methods.

A model for multi-institutional, multidisciplinary sarcoma videoconferencing.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 10521-10521 ◽  
Author(s):  
Steven Attia ◽  
Robert G. Maki ◽  
Jonathan C. Trent ◽  
Scott H. Okuno ◽  
Daniel J. Indelicato ◽  
...  
Keyword(s):  
Surgical Oncology ◽  
Geographic Area ◽  
Tumor Board ◽  
Patient Specific ◽  
Orthopedic Oncology ◽  
Tumor Boards ◽  
Oncology Care ◽  
Evidenced Based ◽  
Management Staff ◽  
Published Research

10521 Background: Sarcomas are rare cancers, with > 50 subtypes, and require multi-disciplinary care. Their management benefits from multi-institutional input due to the paucity of concentrated experience with each subtype. However, sarcoma tumor boards, wherein a patient-specific, consensus treatment approach is determined, are predominantly conducted in isolation at individual centers. Methods: Since March 2010, we have conducted a weekly multi-institutional, multi-disciplinary sarcoma tumor board to combine knowledge and experience in the management of our most challenging patients. The Mayo Clinic bridge links sites by interactive videofeed. Each site may contribute cases. De-identified history, radiology and pathology are reviewed. A didactic series reviews a rotation of seminal papers, newly published research, or our own data. An “Expert Guest" series allows outside experts to connect to one conference. A yearly participant survey assesses quality. Conference is free to sites and is CME accredited. Results: Currently, 8 sarcoma programs connect Mondays from 8-9am ET. Median attendance is 20 (range: 8-27). In 2012, 342 cases were reviewed over 43 conferences (median: 8 cases/conference; range: 4-12 cases/conference). The 2012 survey revealed 96% (25/26) agreed HIPAA rules are followed; 93% (25/27) agreed conference is educational; 93% (25/27) agreed recommendations are evidenced-based or reasonable; 100% (27/27) agreed participants are respectful; and 86% (18/21) agreed input from other sites has changed their management. Staff attendance (quantity) rated as meets/exceeds needs was 100% (25/25) for medical oncology; 96% (26/27) for pathology; 93% (25/27) for orthopedic oncology; 92% (23/25) for radiation oncology, surgical oncology and radiology; and 61% (17/23) for thoracic oncology. Conclusions: To our knowledge, this is the only weekly multi-institutional sarcoma tumor board in existence. It permits consistent oncology care across a wide geographic area, and is a model for providing consensus recommendations regardless of the remoteness of the patient and care team. Future plans for this group include prospective collection of outcomes data.

scholarly journals EPCT-02. COMPARISON OF TARGETED AGENTS RECOMMENDED BY THE CNS-TAP TOOL TO THOSE SELECTED BY A TUMOR BOARD IN A MOLECULARLY-DRIVEN DIPG CLINICAL TRIAL

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i46-i46
Author(s):  
Holly Roberts ◽  
Karthik Ravi ◽  
Bernard Marini ◽  
Cassie Kline ◽  
Sabine Mueller ◽  
...  
Keyword(s):  
Anticancer Agents ◽  
Treatment Plan ◽  
Treatment Options ◽  
Objective Evaluation ◽  
Molecular Profiling ◽  
Diffuse Intrinsic Pontine Glioma ◽  
Tumor Board ◽  
Patient Specific ◽  
Targeted Agents ◽  
Tumor Boards

Abstract Recently, sequencing of diffuse intrinsic pontine glioma (DIPG) biopsy specimens has revealed genomic heterogeneity of these tumors, fueling an interest in individualized, targeted treatment options. The Pacific Pediatric Neuro-Oncology Consortium recently completed enrollment onto a feasibility study PNOC003: Molecular Profiling for Individualized Treatment Plan for DIPG (NCT02274987), in which a multidisciplinary tumor board recommended molecularly-targeted agents based on genomic and molecular profiling of each patient’s tumor. Separately, our group developed the Central Nervous System Targeted Agent Prediction (CNS-TAP) tool, which combines pre-clinical, clinical, and CNS penetration data with patient-specific genomic information to allow for numeric scoring of targeted anticancer agents to objectively evaluate these therapies for use in patients with CNS tumors. We hypothesized that highly-scored agents within CNS-TAP would overlap with the agents recommended by the tumor board in this study. For each PNOC003 participant, we utilized the genomic report to identify actionable alterations and input patient-specific data into CNS-TAP to identify the highest scoring agents. We compared high-scoring agents within CNS-TAP with recommendations from the PNOC003 tumor board for each of the enrolled 28 subjects. Overall, 93% (26/28) of patients had at least one agent recommended by both the tumor board and CNS-TAP. Additionally, 38% (37/95) of all agents recommended by the tumor board were also selected by CNS-TAP. Furthermore, we identified factors that likely contributed to the discordance between these two methods. Without clinician input, CNS-TAP is unable to account for drug-drug interactions, includes only designated anticancer agents, and cannot easily be updated in real time. However, CNS-TAP provides an objective evaluation of targeted therapies, whereas tumor boards are inherently subjective. Given the discordance identified between these methods and the strengths of each, a prospective study incorporating both CNS-TAP and a molecular tumor board for targeted therapy selection in DIPG patients is warranted.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

Virtual Clinical and Precision Medicine Tumor Boards: A Cloud-based Platform-mediated Implementation of Multidisciplinary Reviews among Oncology Centers in the Covid-19 Era. (Preprint)

2020 ◽  
Author(s):  
Livio Blasi ◽  
Roberto Bordonaro ◽  
Vincenzo Serretta ◽  
Dario Piazza ◽  
Alberto Firenze ◽  
...  
Keyword(s):  
Decision Making ◽  
Health Professionals ◽  
Clinical Pathways ◽  
Prospective Trial ◽  
Banking System ◽  
Outcome Data ◽  
Tumor Board ◽  
Time Saving ◽  
Tumor Boards ◽  
Multidisciplinary Tumor Board

BACKGROUND Multidisciplinary tumor boards play a pivotal role in the patients -centered clinical management and in the decision-making process to provide best evidence -based, diagnostic and therapeutic care to cancer patients. Among the barriers to achieve an efficient multidisciplinary tumor board, lack of time and geographical distance play a major role. Therefore the elaboration of an efficient virtual multidisciplinary tumor board (VMTB) is a key-point to reach a successful oncology team and implement a network among health professionals and institutions. This need is stronger than ever in a Covid-19 pandemic scenario. OBJECTIVE This paper presents a research protocol for an observational study focused on exploring the structuring process and the implementation of a multi-institutional VMTB in Sicily. Other endpoints include analysis of cooperation between participants, adherence to guidelines, patients’ outcomes, and patients satisfaction METHODS This protocol encompasses a pragmatic, observational, multicenter, non-interventional, prospective trial. The study's programmed duration is five years, with a half-yearly analysis of the primary and secondary objectives' measurements. Oncology care health-professionals from various oncology subspecialties at oncology departments in multiple hospitals (academic and general hospitals as well as tertiary centers and community hospitals) are involved in a non-hierarchic fashion. VMTB employ an innovative, virtual, cloud-based platform to share anonymized medical data which are discussed via a videoconferencing system both satisfying security criteria and HIPAA compliance. RESULTS The protocol is part of a larger research project on communication and multidisciplinary collaboration in oncology units and departments spread in the Sicily region in Italy. Results of this study will particularly focus on the organization of VMTB involving oncology units present in different hospitals spread in the area and create a network to allow best patients care pathways and a hub and spoke relationship. Results will also include data concerning organization skills and pitfalls, barriers, efficiency, number and type con clinical cases, and customers’ satisfaction. CONCLUSIONS VMTB represents a unique opportunity to optimize patient’s management in a patient centered approach. An efficient virtualization and data banking system is potentially time-saving, a source for outcome data, and a detector of possible holes in the hull of clinical pathways. The observations and results from this VMTB study may hopefully useful to design nonclinical and organizational interventions that enhance multidisciplinary decision-making in oncology.

Patient-specific treatment allocation for carotid artery disease

2009 ◽  
Vol 1 (1) ◽  
pp. 41-49
Author(s):  
Marc Bosiers ◽  
Koen Deloose ◽  
Jurgen Verbist ◽  
Patrick Peeters
Keyword(s):  
Carotid Artery ◽  
Carotid Artery Disease ◽  
Specific Treatment ◽  
Patient Specific ◽  
Treatment Allocation ◽  
Artery Disease

scholarly journals The effect of beta-blockers on hemodynamic parameters in patient-specific blood flow simulations of type-B aortic dissection: a virtual study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohammad Amin Abazari ◽  
Deniz Rafieianzab ◽  
M. Soltani ◽  
Mona Alimohammadi
Keyword(s):  
Aortic Dissection ◽  
Clinical Decision Making ◽  
Beta Blockers ◽  
False Lumen ◽  
Specific Treatment ◽  
Left Ventricular ◽  
Patient Specific ◽  
Type B ◽  
Windkessel Model ◽  
Computed Tomography Images

AbstractAortic dissection (AD) is one of the fatal and complex conditions. Since there is a lack of a specific treatment guideline for type-B AD, a better understanding of patient-specific hemodynamics and therapy outcomes can potentially control the progression of the disease and aid in the clinical decision-making process. In this work, a patient-specific geometry of type-B AD is reconstructed from computed tomography images, and a numerical simulation using personalised computational fluid dynamics (CFD) with three-element Windkessel model boundary condition at each outlet is implemented. According to the physiological response of beta-blockers to the reduction of left ventricular contractions, three case studies with different heart rates are created. Several hemodynamic features, including time-averaged wall shear stress (TAWSS), highly oscillatory, low magnitude shear (HOLMES), and flow pattern are investigated and compared between each case. Results show that decreasing TAWSS, which is caused by the reduction of the velocity gradient, prevents vessel wall at entry tear from rupture. Additionally, with the increase in HOLMES value at distal false lumen, calcification and plaque formation in the moderate and regular-heart rate cases are successfully controlled. This work demonstrates how CFD methods with non-invasive hemodynamic metrics can be developed to predict the hemodynamic changes before medication or other invasive operations. These consequences can be a powerful framework for clinicians and surgical communities to improve their diagnostic and pre-procedural planning.

scholarly journals Towards integration of 64Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2 + breast cancer

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Angela M. Jarrett ◽  
David A. Hormuth ◽  
Vikram Adhikarla ◽  
Prativa Sahoo ◽  
Daniel Abler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Targeted Therapy ◽  
Treatment Response ◽  
Growth Factor Receptor ◽  
Patient Specific ◽  
Mathematical Framework ◽  
Breast Cancer Patients ◽  
Data Types ◽  
Her2 Breast Cancer ◽  
Mri Scans

AbstractWhile targeted therapies exist for human epidermal growth factor receptor 2 positive (HER2 +) breast cancer, HER2 + patients do not always respond to therapy. We present the results of utilizing a biophysical mathematical model to predict tumor response for two HER2 + breast cancer patients treated with the same therapeutic regimen but who achieved different treatment outcomes. Quantitative data from magnetic resonance imaging (MRI) and 64Cu-DOTA-trastuzumab positron emission tomography (PET) are used to estimate tumor density, perfusion, and distribution of HER2-targeted antibodies for each individual patient. MRI and PET data are collected prior to therapy, and follow-up MRI scans are acquired at a midpoint in therapy. Given these data types, we align the data sets to a common image space to enable model calibration. Once the model is parameterized with these data, we forecast treatment response with and without HER2-targeted therapy. By incorporating targeted therapy into the model, the resulting predictions are able to distinguish between the two different patient responses, increasing the difference in tumor volume change between the two patients by > 40%. This work provides a proof-of-concept strategy for processing and integrating PET and MRI modalities into a predictive, clinical-mathematical framework to provide patient-specific predictions of HER2 + treatment response.

scholarly journals How to predict relapse in leukaemia using time series data: A comparative in silico study

2020 ◽  
Author(s):  
Helene Hoffmann ◽  
Christoph Baldow ◽  
Thomas Zerjatke ◽  
Andrea Gottschalk ◽  
Sebastian Wagner ◽  
...  
Keyword(s):  
Data Quality ◽  
Computational Methods ◽  
In Silico ◽  
Prediction Accuracy ◽  
Time Course ◽  
Time Series Data ◽  
Specific Treatment ◽  
Series Data ◽  
Patient Specific ◽  
Clinical Markers

SummaryRisk stratification and treatment decisions for leukaemia patients are regularly based on clinical markers determined at diagnosis, while measurements on system dynamics are often neglected. However, there is increasing evidence that linking quantitative time-course information to disease outcomes can improving the predictions for patient-specific treatment response.We analyzed the potential of different computational methods to accurately predict relapse for chronic and acute myeloid leukaemia, particularly focusing on the influence of data quality and quantity. Technically, we used clinical reference data to generate in-silico patients with varying levels of data quality. Based hereon, we compared the performance of mechanistic models, generalized linear models, and neural networks with respect to their accuracy for relapse prediction. We found that data quality has a higher impact on prediction accuracy than the specific choice of the method. We further show that adapted treatment and measurement schemes can considerably improve prediction accuracy. Our proof-of-principle study highlights how computational methods and optimized data acquisition strategies can improve risk assessment and treatment of leukaemia patients.

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