Details

Autor(en) / Beteiligte

• Eltorai, Adam E. M
• Bakal, Jeffrey A
• Kim, Daniel W
• Wazer, David E

Titel

Translational radiation oncology

Ist Teil von

• Handbook for Designing and Conducting Clinical and Translational Research Series

Auflage

1st ed

Ort / Verlag

San Diego : Elsevier Science & Technology,

Erscheinungsjahr

2023

Link zum Volltext

• Elsevier Books AutoHoldings

Beschreibungen/Notizen

• Front Cover -- Translational Radiation Oncology -- Handbook for Designing and Conducting Clinical and Translational Research -- Translational Radiation Oncology -- Copyright -- Contents -- List of contributors -- Foreword -- Preface -- I - Introduction -- 1 - Introduction -- References -- 2 - Translational process -- Key points -- Why it matters -- Get started -- Pitfalls to avoid -- Real-world examples -- References -- 3 - Scientific method -- Key points -- Why it matters -- Reliability of scientific research -- Get started -- Additional reading -- References -- Further reading -- 4 - Basic research -- Key points -- Why it matters -- Disciplines -- Common lab techniques -- Major areas of current investigation -- Get started -- Resources -- Selected website links -- References -- Further reading -- II - Pre-clinical: Discovery and development -- 5 - Overview of preclinical research -- Key points -- Why it matters? -- Related research -- Methods and techniques -- Control of the expression of genes involved in radiosensitivity via gene knockdown or overexpression -- Short interfering RNA -- Stable knockdown using shRNA -- Stably transfected cell lines -- Determination of cell survival after irradiation -- Function of molecular targets involved in radiosensitivity -- Protein-protein interaction -- (A) In situ proximity ligation assay -- (B) Co-immunoprecipitation -- (C) Confocal microscopy of the distribution of fusion proteins -- Protein decay analysis -- Oligomerization assay -- Ubiquitination assay -- Cell cycle phase detection by flow cytometry analysis -- DNA damage and repair following irradiation -- Oxidative stress on DNA -- Comet assay -- Selection of an appropriate tumor model in animal studies -- Xenograft model -- Allogeneic graft model -- Patient-derived xenograft -- Evaluation of the tumor response -- Tumor growth delay.
• Tumor cure (TCD50) assay -- In vivo imaging system -- Tumor excision for histology examination -- Pitfalls to avoid -- References -- 6 - What problem are you solving? -- Key points -- Why it matters? -- Appropriate target volume delineation -- Optimal constraints of OAR -- Outcome of isolated PALN recurrence -- Pitfalls to avoid -- References -- 7 - Types of interventions: drug, device, diagnostic, procedural technique, or behavior change -- Key points -- Why it matters? -- Drugs complementing the effect of radiotherapy -- Devices for precision radiotherapy -- Motion management -- Proton beam therapy -- Diagnostic tools for target delineation -- Procedural techniques -- Behavior change -- Pitfalls to avoid -- References -- 8 - Drug discovery -- Key points -- Why does it matter? -- Drug discovery in radiation oncology -- Drug discovery process -- Molecular diagnostics -- Major areas of current investigation -- Funding considerations -- Pitfalls to avoid -- Get started -- References -- 9 - Drug testing -- In vitro testing: clonogenic assay and cell survival curve -- In vivo testing -- Laws and regulations for the use of laboratory animals -- Animal tumor model -- Model tumor systems -- Major area of current investigation -- Budgetary considerations -- References -- 10 - Device discovery and prototyping -- Key points -- Why it matters -- Overview -- Prototyping (iterative refinement, optimization process) -- Disciplines and common lab methods/techniques -- Major areas of investigation -- MR Linac -- Rectal spacer -- Nanotechnology -- Budgetary considerations and how to fund this stage -- Non-dilutive sources of funding -- Dilutive sources of funding -- Get started -- Pitfalls -- References -- 11 - Device testing -- Key points -- Why it matters -- Overview -- Classification system for devices -- Safety testing -- Brief overview of FDA submission process.
• Budgetary considerations and how to fund this stage -- Get started -- Potential pitfalls -- Real-world examples -- Resources -- References -- 12 - Diagnostic discovery -- Key points -- Why it matters -- Significant areas of current investigation -- Incorporating diagnostic imaging for radiation therapy planning -- Case study-meningioma -- Predictive biomarkers for radiation therapy -- Molecular signatures -- Circulating tumor DNA -- Theoretical example of a diagnostic discovery study -- Get started -- Potential pitfalls -- References -- 13 - Diagnostic testing -- Key points -- Why it Matters -- Next-generation sequencing -- Proteomics -- Diagnostic testing-real-time PCR -- Get started -- Pitfalls -- Resources and funding sources -- References -- 14 - Procedural technique development in radiation oncology -- Key Points -- Introduction -- Reirradiation -- Stereotaxy -- Flash radiotherapy -- References -- 15 - Behavioral intervention studies in radiation oncology -- Key points -- Why it matters -- The NIH stage model for behavioral intervention development -- Stages -- Stage 0-Basic science research -- Stage I study-Behavioral intervention creation, refinement, and pilot testing -- Assess population needs/issues -- Apply conceptual framework -- Determine study characteristics -- Identify study measures and sample size -- Design core elements of behavioral intervention -- Establish logistics of behavioral intervention delivery -- Dosing of behavioral intervention -- Refinement and pilot testing of behavioral intervention -- Stage II study-Efficacy testing in controlled research setting -- Stage III study-Small-scale efficacy testing in community setting -- Stage IV study-Large-scale effectiveness testing in community setting -- Stage V-Implementation and dissemination research -- Get started -- Best practices and potential pitfalls -- Resources.
• References -- 16 - Artificial intelligence -- Key points -- Why it matters -- The basics of AI and deep learning -- A motivating example -- Machine learning and deep learning -- Training and testing a machine learning model -- Preclinical evaluation of AI -- Clinical evaluation of AI -- Research team and roles -- Radiation oncology and AI -- Treatment decision-making -- Imaging and treatment simulation -- Treatment planning -- Plan approval and quality assurance -- Radiotherapy delivery -- Follow-up care -- Obtaining funding -- Get started -- Pitfalls to avoid -- Resources -- References -- III - Clinical: Fundamentals -- 17 - Introduction to clinical research: What is it? Why is it needed? -- Key points -- Introduction -- References -- 18 - The question: types of research questions and how to develop them -- Why it matters/key points -- What is a research question? -- Types of research questions -- Developing a research question -- Evaluating a research question -- Get started -- Potential pitfalls -- Real-world examples -- Defined terms -- References -- 19 - Defining the study population: who and why? -- Why it matters/key points -- What is the study population? -- How can the study population be defined? -- What are the types of sampling for defining a study population? -- Evaluating a study population -- Get started -- Pitfalls -- Real-world examples -- References -- 20 - Outcome measurements: What data are being collected and why? -- 21 - Optimizing the question: Balancing significance and feasibility: Will the findings affect change? Can that change be implemented in clinical practice? -- Key points -- Why it matters? -- Case-based learning -- Case study 1: designing trials that address a research question of significance and importance -- Case study 2: addressing barriers to accrual and trial completion.
• Case study 3: designing trials conducive to translation into clinical practice -- Get started -- Pitfalls to avoid -- Resources -- References -- 22 - Statistical efficiency in study design -- Key points -- Continuous value or binary cutpoint? -- Time-to-event or landmark time? -- Appendix -- Reference -- IV - Statistical principles -- 23 - Basic statistical principles -- Key points -- Why it matters -- Confidence intervals -- P-values -- Sensitivity and specificity -- Positive and negative predictive values -- Incidence and prevalence -- Odds ratios and risk ratios -- Attributable risks and absolute risk reduction -- Number needed to treat and number needed to harm -- Precision and accuracy -- Get started -- Pitfalls to avoid -- Determining the significance of a P-value -- Interpreting NNT and NNH -- Multiple comparisons and false positives -- Resources -- References -- 24 - Distribution -- Key points -- The normal (Gaussian) distribution -- The standard normal distribution -- Skewness and kurtosis as measures of distribution curve's shape -- Other types of continuous distribution -- Discrete probability distributions -- References -- 25 - Hypotheses and error types -- Key points -- Introduction -- Null hypotheses, alternative hypotheses, and hypothesis testing -- Types of error and mitigation -- Type I Error (α) -- Type II Error (β) -- Get started -- Pitfalls to avoid -- References -- 26 - Power -- Key points -- Introduction -- Factors impacting power calculation -- Clinical trial examples of power -- Pitfalls of power analysis -- Get started -- Conclusions -- Additional resources -- References -- 27 - Regression -- Key points -- Why it matters -- Linear regression -- Definitions -- Variables -- Assumptions of linear regression -- Subjects per variable -- Fitting a linear regression model -- Evaluation metrics for linear regression models.
• Loss functions.
• Translational Radiation Oncology covers the principles of evidence-based medicine and applies them to the design of translational research. The book provides valuable discussions on the critical appraisal of published studies and recent developments in radiation oncology, allowing readers to learn how to evaluate the quality of such studies with respect to measuring outcomes and make effective use of all types of evidence. By reading this book, researchers have access to a practical approach to help them navigate challenging considerations in study design and implementation.
• Description based on publisher supplied metadata and other sources.