Update yourself with the latest advances in Comprehensive Medical Oncology and expand your knowledge in cancer molecular biology, cutting-edge therapies and precision medicine”

The field of Comprehensive Medical Oncology is a constantly evolving specialty due to scientific advances, clinical challenges and the growing demand for comprehensive and multidisciplinary care in cancer management. Medical professionals and specialists dedicated to this specialty face a series of specific novelties and challenges that require constant updating.

Given this context, TECH has created the Advanced master’s degree in Comprehensive Medical Oncology, which offers an advanced and comprehensive update for those physicians and specialists interested in staying current in this constantly evolving specialty. This program provides a wide range of knowledge and skills necessary to address current clinical and scientific challenges in the field of Comprehensive Medical Oncology.

The rationale for participating in this program lies in the need to stay current in the constantly evolving field of Comprehensive Medical Oncology. Advances in the molecular understanding of cancer, the development of new therapies and treatment approaches, as well as the growing importance of comprehensive and multidisciplinary care in cancer management make it essential to have an updated and complete instruction in this specialty.

The Advanced master’s degree in Comprehensive Medical Oncology offers a wide range of topics, including the molecular biology of cancer, advances in diagnosis and treatment, genomic data mining techniques, psycho-oncological care, radiotherapy and psychological treatments in cancer and third generation therapies. Participants will have the opportunity to update their knowledge and gain a comprehensive, multidisciplinary perspective on cancer management.

An outstanding advantage of this program is that it is taught 100% online, which allows participants to access the Virtual Campus from anywhere and at any time, adapting to their schedules and professional responsibilities. In addition, the program uses innovative educational methodologies, such as clinical simulations and case discussions, which allow participants to practically apply the knowledge acquired and strengthen their clinical skills.

Delve into multidisciplinary approaches to comprehensive cancer management, addressing clinical, psycho-oncological and side effect management aspects”

This Advanced master’s degree in Comprehensive Medical Oncology contains the most complete and up-to-date scientific program on the market. The most important features include:

• The development of case studies presented by experts in oncology
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies in cancer management
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

Delve into the latest techniques in the genomic era, use of Unix and Linux in bioinformatics, data analysis in Big Data projects with R for an updated and cutting-edge clinical practice” 

Includes in its teaching staff professionals belonging to the oncology field, who pour into this program the experience of their work, in addition to recognized specialists from reference societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide an immersive learning experience designed to prepare for real-life situations.

This program is designed around Problem-Based Learning, whereby the student must try to solve the different professional practice situations that arise throughout the program. For this purpose, the professional will be assisted by an innovative interactive video system created by renowned and experienced experts.

Expand your knowledge in specific cancers such as breast, lung, ENT, colorectal, gynecological, urological, sarcoma, melanoma and brain cancers"

Analyze assessment and measurement instruments in psycho-oncology, communication with the oncology patient and bereavement management"

The Advanced master’s degree in Comprehensive Medical Oncology has a carefully designed structure and content to offer a complete and enriching learning experience. The program includes a variety of multimedia resources, detailed videos, complementary readings and clinical guides that provide an innovative and effective approach in the process of updating participants.

You will have access to a wide variety of multimedia resources such as interactive presentations, in-depth videos and recorded lessons, which offer a dynamic and visual approach to learning”

Module 1. Molecular Biology

1.1. Molecular Mechanisms of Cancer

1.1.1. Cellular Cycle
1.1.2. Detachment of Tumor Cells

1.2. Reprogramming of the Tumor Microenvironment

1.2.1. Tumor Microenvironments: An Overview
1.2.2. TME as a Prognostic Factor in Lung Cancer
1.2.3. TME in the Progression and Metastasis of Lung Cancer

1.2.3.1. Cancer-Associated Fibroblasts (CAF)
1.2.3.2. Endothelial Cells
1.2.3.3. Hypoxia in Lung Cancer
1.2.3.4. Inflammation
1.2.3.5. Immune Cells

1.2.4. Contribution of TME to Therapeutic Resistance

1.2.4.1. Contribution of TME to Radiotherapy Resistance

1.2.5. TME as a Target Treatment in Lung Cancer

1.2.5.1. Future Directions

1.3. Tumor Immunology: Basis of Cancer Immunotherapy

1.3.1. Introduction to the Immune System
1.3.2. Tumor Immunology

1.3.2.1. Tumor-Associated Antigens
1.3.2.2. Identification of Tumor-Associated Antigens
1.3.2.3. Types of Tumor-Associated Antigens

1.3.3. The Bases of Immunotherapy in Cancer

1.3.3.1. Introduction to the Immunotherapeutic Approaches
1.3.3.2. Monoclonal Antibodies in Cancer Therapy

1.3.3.2.1. Production of Monoclonal Antibodies
1.3.3.2.2. Types of Therapeutic Antibodies
1.3.3.2.3. Mechanisms of Action of Antibodies
1.3.3.2.4. Modified Antibodies

1.3.4. Non-Specific Immune Modulators

1.3.4.1. Bacillus of Calmette-Guérin
1.3.4.2. Interferon-α
1.3.4.3. Interleucina-2
1.3.4.4. Imiquimod

1.3.5. Other Approaches for Immunotherapy

1.3.5.1. Dendritic Cell Vaccines
1.3.5.2. Sipuleucel-T
1.3.5.3. CTLA-4 Blocking
1.3.5.4. Adoptive T-cell Therapy

1.3.5.4.1. Adoptive Cell Therapy With T-cell Clones
1.3.5.4.2. Adoptive Cell Therapy With Tumor-Infiltrating Lymphocytes

1.4. Molecular Mechanisms Involved in the Invasion and Metastasis Process

Module 2. Genomic or precision oncology

2.1. Use of Gene Expression Profiling in Cancer
2.2. Molecular Subtypes of Breast Cancer
2.3. Prognostic-Predictive Genomic Platforms in Breast Cancer
2.4. Therapeutic Targets in Non-Small Cell Lung Cancer

2.4.1. Introduction
2.4.2. Molecular Detection Techniques
2.4.3. EGFR Mutation
2.4.4. ALK Translocation
2.4.5. ROS Translocation
2.4.6. BRAF Mutation
2.4.7. NRTK Rearrangements
2.4.8. HER2 Mutation
2.4.9. MET Mutation/Amplification
2.4.10. RET Rearrangements
2.4.11. Other Molecular Targets

2.5. Molecular Classification of Colon Cancer
2.6. Molecular Studies in Gastric Cancer

2.6.1. Treatment of Advanced Gastric Cancer
2.6.2. HER2 Overexpression in Advanced Gastric Cancer
2.6.3. Identification and Interpretation of HER2 Overexpression in Advanced Gastric Cancer
2.6.4. Drugs With Activity Against HER2
2.6.5. Trastuzumab in the First Line of Advanced Gastric Cancer

2.6.5.1. Treatment of HER2+ Advanced Gastric Cancer After Progression to Trastuzumab-Based Regimens
2.6.6. Activity of Other Anti-HER2 Drugs in Advanced Gastric Cancer

2.7. GIST as a Model of Translational Research: 15 Years of Experience

2.7.1. Introduction
2.7.2. Mutations of KIT and PDGFRA as Major Promoters in GIST
2.7.3. Genotype in GIST: Prognostic and Predictive Value
2.7.4. Genotype in GIST and Resistance to imatinib
2.7.5. Conclusions

2.8. Molecular and Genomic Biomarkers in Melanoma
2.9. Molecular Classification of Brain Tumors
2.10. Molecular and Genomic Biomarkers in Melanoma
2.11. Immunotherapy and Biomarkers

2.11.1. Landscape of Immunological Therapies in Cancer Treatment and the Need to Define the Mutational Profile of a Tumor
2.11.2. Checkpoint Inhibitor Biomarkers: PD-L1 and Beyond

2.11.2.1. The Role of PD-L1 in Immune Regulation
2.11.2.2. Clinical Trial Data and PD-L1 Biomarker
2.11.2.3. Thresholds and Assays for PD-L1 Expression: a Complex Picture
2.11.2.4. Budding Biomarkers

2.11.2.4.1. Tumor Mutational Burden (TMB)

2.11.2.4.1.1. Quantification of the Tumor Mutational Burden
2.11.2.4.1.2. Evidence of the Tumor Mutational Burden
2.11.2.4.1.3. Tumor Burden as a Predictive Biomarker
2.11.2.4.1.4. Burden as a Prognosis Biomarker
2.11.2.4.1.5. The Future of the Mutational Burden

2.11.2.4.2. Microsatellite Instability
2.11.2.4.3. Immune Infiltrate Analysis
2.11.2.4.4. Toxicity Markers

2.11.3. Immune Checkpoint Drug Development in Cancer
2.11.4. Available Drugs

Module 3. Changes in Current Clinical Practice and New Applications With Genomic Oncology

3.1. Liquid Biopsies: Fashion or Future?

3.1.1. Introduction
3.1.2. Circulating Tumor Cells
3.1.3. ctDNA
3.1.4. Clinical Applications
3.1.5. CtDNA Limitations
3.1.6. Conclusions and Future

3.2. Role of the Biobank in Clinical Research

3.2.1. Introduction
3.2.2. Is it Worth the Effort to Create a Biobank?
3.2.3. How to Begin Establishing a Biobank?
3.2.4. Informed Consent for the Biobank
3.2.5. Collecting Samples for the Biobank
3.2.6. Quality Control
3.2.7. Access to Samples

3.3. Clinical trials: New Concepts Based on Precision Medicine

3.3.1. What Are Clinical Trials? What Sets Them Apart From Other Types of Research?

3.3.1.1. Types of Clinical Trials

3.3.1.1.1. By Their Objectives
3.3.1.1.2. By The Number of Partaking Centers
3.3.1.1.3. By Their Methodology
3.3.1.1.4. By Their Level of Masking

3.3.2. Results of Clinical Trials in Thoracic Oncology

3.3.2.1. Related to Survival Time
3.3.2.2. Results Related to the Tumor
3.3.2.3. Results Notified by the Patient

3.3.3. Clinical Trials in the New Age of Precision Medicine

3.3.3.1. Precision Medicine
3.3.3.2. Terminology Relate to the Design of Trials in the Era of Precision Medicine

3.4. Incorporation of Actionable Markers in Clinical Practice
3.5. Application of Genomics in Clinical Practice by Type of Tumor
3.6. Decision support Systems in Oncology Based on Artificial Intelligence

Module 4. Use of Unix and Linux in Bioinformatics

4.1. Introduction to the Linux Operating System

4.1.1. What is an Operating System?
4.1.2. The Benefits of Using Linux

4.2. Linux Environment and Installation

4.2.1. Linux Distributions
4.2.2. Linux Installation Using a USB Memory
4.2.3. Linux Installation Using a CD-ROM
4.2.4. Linux Installation Using an Virtual Machine

4.3. The Command Line

4.3.1. Introduction
4.3.2. What is a Command Line?
4.3.3. Working on the Terminal
4.3.4. Shell and Bash

4.4. Basic Browsing

4.4.1. Introduction
4.4.2. How to Learn the Current Location?
4.4.3. Absolute and Relative Routes
4.4.4. How to Navigate in the System?

4.5. File Manipulation

4.5.1. Introduction
4.5.2. How to Build a Directory?
4.5.3. How to Move to a Directory?
4.5.4. How to Create an Empty File?
4.5.5. Copying a File and Directory
4.5.6. Deleting a File and Directory

4.6. VI Text Editor

4.6.1. Introduction
4.6.2. How to Save and Exit?
4.6.3. How to Browse a File in the VI Text Editor?
4.6.4. Deleting Contents
4.6.5. The Undo Command

4.7. Wildcards

4.7.1. Introduction
4.7.2. What are Wildcards?
4.7.3. Examples of Wildcards

4.8. Licences

4.8.1. Introduction
4.8.2. How to See the Licences of a File?
4.8.3. How to Change the Licences?
4.8.4. Licence Configuration
4.8.5. Licences for Directories
4.8.6. The “Root” User

4.9. Filters

4.9.1. Introduction
4.9.2. Head
4.9.3. Tail
4.9.4. Sort
4.9.5. nl
4.9.6. wc
4.9.7. cut
4.9.8. sed
4.9.9. uniq
4.9.10. tac
4.9.11. Other Filters

4.10. Grep and Common Expressions

4.10.1. Introduction
4.10.2. eGrep
4.10.3. Common Expressions
4.10.4. Some Examples

4.11. Pipelines and Redirection

4.11.1. Introduction
4.11.2. Redirect to a File
4.11.3. Save a File
4.11.4. Redirect From a File
4.11.5. STDERR Redirection
4.11.6. Pipelines

4.12. Managing Processes

4.12.1. Introduction
4.12.2. Active Processes
4.12.3. Closing a Corrupt Program
4.12.4. Foreground and Background Work

4.13. Bash

4.13.1. Introduction
4.13.2. Important Points
4.13.3. Why “./ ”?
4.13.4. Variables
4.13.5. The Declarations

Module 5. Data analysis in Big Data projects: R programming language

5.1. Introduction to R programming language

5.1.1. What is R?
5.1.2. R Installation and the Graphic Interface of R
5.1.3. Packages

5.1.3.1. Standard Packages
5.1.3.2. Contributed Packages and CRAN

5.2. Basic Features of R

5.2.1. The Environment of R
5.2.2. Software and Related Documentation
5.2.3. R and Statistics
5.2.4. R and the Window System
5.2.5. Using R Interactively
5.2.6. An Introductory Session
5.2.7. Obtaining Help With Functions and Features
5.2.8. R Commands, Cap Sensitivity, etc
5.2.9. Recovery and Correction of Previous Commands
5.2.10. Execute Commands or Diverting the Output to a File
5.2.11. Data Storage and Object Deletion

5.3. Types of Objects in R

5.3.1. Simple Manipulations; Numbers and Vectors

5.3.1.1. Vectors and Their Assignment
5.3.1.2. Vector Arithmetic
5.3.1.3. Generating Regular Sequences
5.3.1.4. Logical Vectors
5.3.1.5. Lost Values
5.3.1.6. Character Vectors
5.3.1.7. Index Vectors

5.3.1.7.1. Selecting and Modifying Subsets of a Dataset

5.3.1.8. Other Types of Objects

5.3.2. Objects, Their Modes and Attributes

5.3.2.1. Intrinsic Attributes: Mode and Length
5.3.2.2. Changing the Length of an Object
5.3.2.3. Obtaining and Configuring Attributes
5.3.2.4. The Class of an Object

5.3.3. Sorted and Unsorted Factors

5.3.3.1. A Specific Example
5.3.3.2. The Tapply () Function and Unequal Matrices
5.3.3.3. Sorted Factors

5.3.4. Matrices

5.3.4.1. Matrices
5.3.4.2. Matrix Indexation. The Subsections of a Matrix
5.3.4.3. Index Matrices
5.3.4.4. The Array () Function
5.3.4.5. Mixed Arithmetic of Vectors and Matrices. The Recycling Rule
5.3.4.6. The Outer Product of Two Matrices
5.3.4.7. The General Transposition of a Matrix
5.3.4.8. Matrix Multiplication
5.3.4.9. Eigenvalues and Eigenvectors
5.3.4.10. Decomposition of Singular Values and Determinants
5.3.4.11. Forming Partitioned Matrices, Cbind () and Rbind ()
5.3.4.12. The Concatenation Function, c (), With Matrices

5.3.5. Factor Frequency Tables
5.3.6. Lists

5.3.6.1. Creating and Modifying Lists
5.3.6.2. Concatenation Lists

5.3.7. DataFrames

5.3.7.1. How to Create DataFrames?
5.3.7.2. Attach () and Separate ()
5.3.7.3. Working With DataFrames

5.4. Reading and Writing Data

5.4.1. The Read.Table () Function
5.4.2. The Scan () Function
5.4.3. Access to the Sets of Incorporated Data
5.4.4. Loading Data From Other R Packages
5.4.5. Editing Data

5.5. Grouping, Loops and Conditional Execution

5.5.1. Grouped Expressions
5.5.2. Control Statements

5.5.2.1. Conditional Execution: IF Sentences
5.5.2.2. Repetitive Execution: For Loops, Repetition and Time

5.6. Writing Your Own Functions

5.6.1. Simple Examples
5.6.2. Defining New Binary Operators
5.6.3. Arguments With Name and Default Value
5.6.4. Argument “...” 0
5.6.5. Assignments Within Functions

Module 6. Graphical Environment in R

6.1. Graphical Procedures

6.1.1. High-Level Plotting Commands

6.1.1.1. The Plot () Function
6.1.1.2. Multivariate Data Visualization
6.1.1.3. Screen Graphics
6.1.1.4. High-Level Plotting Arguments

6.1.2. Low-Level Plotting Commands

6.1.2.1. Mathematical Annotation
6.1.2.2. Hershey Vectorial Sources

6.1.3. Interacting With Graphics
6.1.4. The Use of Graphic Parameters

6.1.4.1. Permanent Changes: the Par () Function
6.1.4.2. Temporary Changes: Arguments to Graphic Functions

6.1.5. List of Graphic Parameters

6.1.5.1. Graphical Elements
6.1.5.2. Axles and Markings
6.1.5.3. Figure Margins
6.1.5.4. Multi-Figure Environment
6.1.6. Descriptive Statistics: Graphical Representations

Module 7. Statistical analysis in R

7.1. Discrete Probability Distributions
7.2. Continuous Probability Distributions
7.3. Introduction to Inference and Sampling (Point Estimate)
7.4. Confidence Intervals
7.5. Hypothesis Testing
7.6. ANOVA of a Factor
7.7. Adjustment kindness (Chi-- Square Test)
7.8. Fitdist Package
7.9. Introduction to Multivariant Statistics

Module 8. Machine Learning for Analysing Big Data

8.1. Introduction to Machine Learning
8.2. Presentation of the Problem, Loading Data and Libraries
8.3. Data Cleaning (Nas, Categories, Dummy Variables)
8.4. Exploratory Data Analysis (ggplot) + Crossed Validation
8.5. Prediction Algorithms: Multiple Linear Regression, Support Vector Machine, Regression Trees, Random Forest
8.6. Classification Algorithms: Logistic Regression, Support Vector Regression, Classification Trees, Random Forest…
8.7. Adjustment of the Hyper Parameters of the Algorithm
8.8. Predicting Data with Different Models
8.9. ROC Curves and Confusion Matrices for Assessing Model Quality

Module 9. Data Mining Applied to Genomics

9.1. Introduction
9.2. Initiation to Variables
9.3. Text Cleaning and Conditioning
9.4. Generating the Word Matrix
9.4.1. Creating the TDM Word Matrix
9.4.2. Visualizations on the TDM Word Matrix
9.5. Description of the Word Matrix

9.5.1. Graphic Representation of the Frequencies
9.5.2. Creating a Word Cloud

9.6. Creating a Data Frame for K-NN
9.7. Creating a Classification Model
9.8. Validating a Classification Model
9.9. Guided Practical Exercise on Data Mining in Cancer Genomics

Module 10. Techniques for extracting genomic data

10.1. Introduction to "Scraping Data"
10.2. Importing Spreadsheet Data Files Stored Online
10.3. Scraping HTML Text
10.4. Scraping Data from an HTML Table
10.5. Using APIs for Data Scraping
10.6. Extracting Relevant Information
10.7. Using the Rvest Package of R
10.8. Obtaining Data Distributed Over Multiple Pages
10.9. Extracting Genomic Data from the “My Cancer Genome” Platform
10.10. Extracting Information on Genes from the HGNC HUGO Gene Nomenclature Committee Database
10.11. Extracting Pharmacological Data from the “OncoKG" (Precision Oncology Knowledge Base) Database

Module 11. New techniques in the age of genomics

11.1. Understanding the New Technology: Next Generation Sequence (NGS) in clinical practice

11.1.1. Introduction
11.1.2. Background
11.1.3. Problems in the Application of Sanger Sequencing in Oncology
11.1.4. New Sequencing Techniques
11.1.5. Advantages of Using NGS in Clinical Practice
11.1.6. Limitations of Using NGS in Clinical Practice
11.1.7. Terms and Definitions of Interest
11.1.8. Types of Studies Depending on Their Size and Depth

11.1.8.1. Genome
11.1.8.2. Exomes
11.1.8.3. Multigenic Panels

11.1.9. Stages of NGS Sequencing

11.1.9.1. Preparing Samples and Libraries
11.1.9.2. Preparing Templates and Sequencing
11.1.9.3. Bioinformatic Processing

11.1.10. Annotation and Classification of Variants

11.1.10.1. Population Databases
11.1.10.2. Locus-Specific Databases
11.1.10.3. Bioinformatic Predictors of Functionality

11.2. DNA Sequencing and Bioinformatic Analysis

11.2.1. Introduction
11.2.2. Software
11.2.3. Procedure

11.2.3.1. Extracting Raw Sequences
11.2.3.2. Aligning Sequences
11.2.3.3. Alignment Refinement
11.2.3.4. Variant Call
11.2.3.5. Variant Filtering

11.3. RNA Sequencing and Bioinformatic Analysis

11.3.1. Introduction
11.3.2. Software
11.3.3. Procedure

11.3.3.1. QC Evaluation of Raw Data
11.3.3.2. RNAr Filtering
11.3.3.3. Filtered Quality Control Data
11.3.3.4. Quality Trimming and Adapter Removal
11.3.3.5. Alignment of Reads to a Reference
11.3.3.6. Variant Call
11.3.3.7. Differential Gene Expression Analysis

11.4. ChIP-seq Technology

11.4.1. Introduction
11.4.2. Software
11.4.3. Procedure

11.4.3.1. CHIP-seq Data Set Description
11.4.3.2. Obtaining Information About the Experiment Using the GEO and SRA Websites
11.4.3.3. Quality Control of the Sequencing Data
11.4.3.4. Trimming and Filtering Reads
11.4.3.5. Visualizing Results with the Integrated Genonme Browser (IGV)

11.5. Big Data Applied to Oncology Genomics

11.5.1. The Process of Analysis Data

11.6. Genomic Servers and Databases of Genetic Variants

11.6.1. Introduction
11.6.2. Online Genomic Servers
11.6.3. Genomic Server Architecture
11.6.4. Recuperation and Data Analysis
11.6.5. Personalization

11.7. Annotation of Genetic Variants

11.7.1. Introduction
11.7.2. What is Variant Calling?
11.7.3. Understanding the VCF Format
11.7.4. Variant Identification
11.7.5. Variant Analysis
11.7.6. Predicting the Effect of the Variation of a Protein’s Structure and Function

Module 12. Application of bioinformatics in genomic oncology

12.1. Clinical and Pharmacological Enrichment of Gene Variants
12.2. Mass Search in PubMed for Genomic Information
12.3. Mass Search in DGIdb for Genomic Information
12.4. Mass Search in Clinical Trials for Clinical Trials on Genomic Data
12.5. Gene Similarity Search for the Interpretation of a Gene Panel or Exome
12.6. Mass Search for Genes Connected to a Disease
12.7. Enrich-Gen: Platform for the Clinical and Pharmacological Enrichment of Genes
12.8. Procedure to Produce a Genomic Report in the Age of Precision Oncology

Module 13. Breast Cancer

13.1. Principles of Breast Cancer

13.1.1. Epidemiology
13.1.2. Risk Factors

13.2. Screening
13.3. Diagnosis

13.3.1. Clinical Introduction and Diagnosis

13.4. Staging
13.5. Subtypes
13.6. Treatment of Luminal Disease

13.6.1. Localized Disease
13.6.2. Advanced Disease

13.7. Treatment of HER 2 Disease

13.7.1. Localized Disease
13.7.2. Advanced Disease

13.8. Treatment of Triple Negative Disease

13.8.1. Localized Disease
13.8.2. Advanced Disease

13.9. Future Prospects for Luminal Disease
13.10. Future Prospects for Non-Luminal Disease

Module 14. Lung Cancer

14.1. Principles of Lung Cancer

14.1.1. Epidemiology
14.1.2. Risk Factors

14.2. Major Mutations: Potential Targets
14.3. Diagnosis
14.4. Staging
14.5. Treatment of Microcytic Cancer with Localized Disease
14.6. Treatment of Microcytic Cancer with Widespread Disease
14.7. Treatment of non-small Cell Lung Cancer Localized Disease
14.8. Treatment of non-small Cell Lung Cancer Advanced Disease

14.8.1. Adenocarcinoma
14.8.2. Squamous cell carcinoma

14.9. Future Perspectives
14.10. Primary prevention

Module 15. ORL tumours

15.1. ORL Cancer

15.1.1. Epidemiology
15.1.2. Risk Factors

15.2. Major Mutations: Potential Targets
15.3. Diagnosis
15.4. Staging
15.5. Treatment of Localized Laryngeal Tumors
15.6. Treatment of Pharynx Tumors
15.7. Treatment of Advanced ORL Tumors
15.8. Treatment of Localized Cavum Tumors
15.9. Treatment of Advanced Cavum Tumors
15.10. Future Perspectives

Module 16. Colorectal cancer and anal canal

16.1. Colon and anal canal

16.1.1. Epidemiology
16.1.2. Risk Factors

16.2. Diagnosis
16.3. Staging
16.4. Treatment of Localized Disease Colon Cancer
16.5. Treatment of Localized Rectal Cancer
16.6. Treatment of Advanced Disease Colorectal Cancer
16.7. Treatment of Anal Canal Tumors
16.8. Future Perspectives
16.9. Screening
16.10. Genetic Associate Syndromes

Module 17. Non-colorectal digestive tumors

17.1. Non-colorectal digestive tumors

17.1.1. Epidemiology
17.1.2. Risk Factors

17.2. Diagnosis
17.3. Staging

17.3.1. Oesophageal Cancer
17.3.2. Stomach Cancer
17.3.3. Pancreatic Cancer

17.4. Oesophageal Cancer

17.4.1. Localized Disease Treatment
17.4.2. Treatment of Extended Disease

17.5. Stomach Cancer

17.5.1. Localized Disease Treatment
17.5.2. Treatment of Extended Disease

17.6. Pancreatic Cancer

17.6.1. Localized Disease Treatment
17.6.2. Treatment of Extended Disease

17.7. Biliary Tract Cancer
17.8. Hepatocellular Carcinoma
17.9. Neuroendocrine Tumors
17.10. Future Perspectives

Module 18. Gynecologic Tumors

18.1. Gynecologic Tumors

18.1.1. Epidemiology
18.1.2. Risk Factors

18.2. Diagnosis
18.3. Staging

18.3.1. Ovarian Cancer
18.3.2. Cervical Cancer
18.3.3. Endometrial Cancer

18.4. Treatment of Localized Ovarian Cancer
18.5. Advanced Ovarian Cancer Treatment
18.6. Localized Uterine Cancer Treatment

18.6.1. Cervix
18.6.2. Endometrium

18.7. Advanced Uterus Cancer Treatment

18.7.1. Cervix
18.7.2. Endometrium

18.8. Uterine Sarcomas
18.9. Genetic Syndromes
18.10. Future Perspectives

Module 19. Urological tumors

19.1. Evolution

19.1.1. Epidemiology

19.2. Diagnosis

19.2.1. Prostate Cancer
19.2.2. Urothelial Cancer
19.2.3. Renal Cancer
19.2.4. Testicular Cancer

19.3. Staging

19.3.1. Prostate Cancer
19.3.2. Urothelial Cancer
19.3.3. Renal Cancer

19.4. Localized Prostate Cancer Treatment
19.5. Advanced Prostate Cancer Treatment
19.6. Localized Urothelial Cancer Treatment
19.7. Advanced Urothelial Cancer Treatment
19.8. Renal Cancer Treatment
19.9. Testicular Cancer Treatment
19.10. Penile Cancer

Module 20. Sarcomas and melanomas

20.1. Principles of Mesenchymal Tumors
20.2. Diagnosis of Mesenchymal Tumors
20.3. Surgical Treatment of Bone and Soft Tissue Tumors
20.4. Sarcoma Medical Treatment

20.4.1. Bones
20.4.2. Soft Parts

20.5. Treatment of GIST
20.6. Melanoma
20.7. Diagnosis and Staging Melanoma
20.8. Localized Melanoma Treatment
20.9. Advanced Melanoma Treatment
20.10. Future Perspectives

20.10.1. Bone and Soft Tissue Tumors
20.10.2. Melanoma

Module 21. Brain Tumors

21.1. Evolution

21.1.1. Epidemiology

21.2. Classification
21.3. Genetic Associate Syndromes
21.4. Prognostic and Predictive Response Factors
21.5. Diagnosis
21.6. Treatment of Low Grade Tumors
21.7. Treatment of High Grade Tumors
21.8. Immunotherapy
21.9. Cerebral Metastases
21.10. Future Perspectives

Module 22. Radiotherapy

22.1. Evolution
22.2. Types of Radiotherapy
22.3. Treatment of Breast Cancer
22.4. Treatment of Lung Cancer
22.5. Treatment of Prostate Cancer
22.6. Treatment of Digestive Tumors
22.7. Treatment of Brain Tumors 
22.8. Treatment of ORL Tumors
22.9. Orbital Tumors, Mediastinal Tumors, Mesenchymal Tumors
22.10. Palliative Radiotherapy

Module 23. Characterization and Fields of Application of Psycho-Oncology

23.1. Cancer and Its Impact on Current Society

23.1.1. Cultural Variability
23.1.2. Incidence, Prevalence and Mortality

23.2. Myths, Beliefs and Pseudotherapies Related to Cancer
23.3. Medical Care for Cancer Patients

23.3.1. Early Detection of Cancer
23.3.2. Surgery and Treatment

23.4. Risk Factors and Cancer

23.4.1. Psychoneuroimmunology
23.4.2. Stress, Coping Styles and Personality Variables

23.5. Cancer Prevention

23.5.1. Primary and Secondary Prevention
23.5.2. Health Education and Healthy Lifestyle Habits

23.6. Functions of the Psycho-Oncologist: Their Role Within the Hospital Environment
23.7. Teaching, Training, Specialization and Accreditation in Psycho-Oncology
23.8. Objectives and Areas of Psychological Intervention for Cancer Patients and their Families
23.9. Other Disciplines Related to Psycho-Oncology

23.9.1. Psychology as an Intersection Between Oncology and Health Psychology

23.10. Approach to the Social Needs of the Cancer Patient

23.10.1. Economic and Occupational Impact. Job Reintegration
23.10.2. Social Support and Cancer

Module 24. Psychological Treatments in Cancer and Third Generation Therapies

24.1. Effective Psychological Treatments in Psycho-Oncology
24.2. Cognitive-Behavioral Therapy in Cancer Treatment

24.2.1. Identification of Automatic Thoughts and Modification of Cognitions
24.2.2. Activation Control Techniques

24.2.2.1. Diaphragmatic Breathing Training
24.2.2.2. Progressive Muscular Relaxation

24.2.3. Behavioral Activation
24.2.4. Exposition Techniques and Guided Imagination

24.3. Cognitive Training Program
24.4. Rehabilitation Program Based on Physical Exercise
24.5. Mindfulness

24.5.1. Mindfulness Training Program
24.5.2. Compassion and Self-Compassion Practice

24.6. Acceptance and Commitment Therapy (ACT)

24.6.1. Components of ACT and Clinical Methods

24.7. Therapy Focused on the Search for Meaning

24.7.1. Cancer and Feeling. Exploration of the Sources of Meaning

24.8. Dignity Therapy

24.8.1. The Concept of Dignity in Cancer Patients
24.8.2. Models of Dignity. Chochinov

24.9. Systemic Family Therapy

24.9.1. Family and Cancer. Most Common Family Dynamics

24.10. Pseudotherapies and Pseudosciences Against Cancer

24.10.1. Positions of Government Agencies
24.10.2. Pseudotherapies and Pseudosciences With and Without Scientific Evidence

Module 25. Most Relevant Psychological Aspects According to Different Tumor Locations

25.1. Leukemias, Lymphomas and Myelomas

25.1.1. Bone Marrow Transplantation and Isolation Situations

25.2. Breast Cancer and Gynecology

25.2.1. Body image
25.2.2. Sexuality
25.2.3. Self-esteem
25.2.4. Chemobrain Effect

25.3. Prostate Cancer

25.3.1. Incontinence and Sexual Impotence

25.4. Colon Cancer and the Digestive System

25.4.1. Living with a Colostomy

25.5. Intervention in Laryngectomized Patients

25.5.1. Speech Therapy Intervention
25.5.2. Alteration in Social and Work Life

25.6. Head and Neck Tumors
25.7. Thyroid Cancer
25.8. Tumors of the Central Nervous System

25.8.1. Cognitive Deficits and Mobility Limitations

25.9. Lung Cancer
25.10. Child Cancer

25.10.1. Emotional Development and Child Intellect
25.10.2. Social Impact on the Child
25.10.3. Impact on the Family

Module 26. Protocols for Emotional Intervention at the End of Life

26.1. Palliative Care Objectives
26.2. Evaluation of Suffering
26.3. Process of Psychosocial Adaptation at the End of Life

26.3.1. Adaptive vs. Maladaptive Reactions

26.4. Triadic Interaction Model for Patients, Family and Healthcare Professionals
26.5. Specific Interventions Centered on the Patient

26.5.1. Anxiety
26.5.2. Sadness
26.5.3. Hostility
26.5.4. Fear
26.5.5. Blame
26.5.6. Denial
26.5.7. Withdrawal

26.6. Specific Needs of the Family. Assessment of the Patient-Family Unit

26.6.1. Conspiracy of Silence
26.6.2. Family Claudication

26.7. Interventions Oriented Towards Health Professionals

26.7.1. Working in Multicultural Teams
26.7.2. Prevention of Burnout Syndrome

26.8. Attention to the Spiritual Needs of the Patient

26.8.1. Spiritual Care Model of SECPAL (Spanish Society of Palliative Care)
26.8.2. Existential Angst and Religious Experience

26.9. Psychological Intervention in Pediatric Palliative Care
26.10. Advance Decision Making Process and Planning (ADP)

26.10.1. Declaration and Registry of Advance Vital Wills

Module 27. Evaluation and Measurement Instruments

27.1. The Psycho-Oncology Clinical Interview
27.2. Evaluation of the Needs of the Cancer Patient

27.2.1. Needs Evaluation Questionnaire, (NEQ)
27.2.2. Patient Needs Assessment Tool, (PNAT)
27.2.3. The Short-Form Cancer Needs Questionnaire, (CNQ)

27.3. Evaluation of the Quality of Life of the Cancer Patient

27.3.1. EORTC Questionnaire (European Organization for Research and Therapy of Cancer)
27.3.2. FACT Questionnaire (Functional Assessment of Cancer Therapy)
27.3.3. SF 36 Health Questionnaire

27.4. Main Evaluation Questions for Physical Symptoms of Cancer

27.4.1. Edmonton Symptom Assessment Sytem (ESAS)
27.4.2. Questions for Pain Assessment
27.4.3. Questions for Fatigue and Quality of Sleep Evaluation
27.4.4. Cognitive Screening and Functional State Questionnaires
27.4.5. Questionnaires for the Evaluation of Sexuality

27.5. Detection of Distress and Assessment of Suffering

27.5.1. Emotional Distress Screening Questionnaire
27.5.2. Emotional Distress Thermometer
27.5.3. Hospital Anxiety and Depression Scale (HAD)
27.5.4. Subjective Perception of the Passing of Time
27.5.4.1. Waiting Times in Oncology

27.6. Socio-Familial Assessment and Valuation

27.6.1. Perceptoin of the Family Function. APGAR Family Questionnaire
27.6.2. Family Relationship Index (FRI)
27.6.3. Self Report Family Inventory (SFI)

27.7. Coping Assessment Questionnaires for Cancer Patients

27.7.1. Mental Adjustment to Cancer (MAC)
27.7.2. Questionnaire to Measure Coping Styles. Miller Behavioral Style Scale (MBSS)
27.7.3. COPE Questionnaire

27.8. Assessment Tools for Spiritual Needs

27.8.1. Spiritual Needs and Well-Being Assessment Scale from GES (Spiritual Group). Part of SEPCAL (Spanish Society for Palliative Care)
27.8.2. Functional Assessment of Chronic Illness Therapy Spiritual Well Being
27.8.3. The Patient Dignity Inventory

27.9. Self-Report and Observation

27.9.1. Clinical Case Formulation
27.10. Psychological Assessment of Children in Palliative Care

Module 28. Communication with the Oncologic Patient

28.1. Illness, Communication and the Helping Relationship

28.1.1. Doctor-Patient Communication as a Possible Factor of Improvement and Iatrogenesis. Pain and Suffering Prevention
28.1.2. Communication Barriers

28.2. How to Give Bad News About Cancer

28.2.1. Answers to Difficult Questions
28.2.2. Communication in Complicated Situations

28.3. Counselling Techniques in Clinical Practice

28.3.1. Counselling Attitudes
28.3.2. Assertive Communication
28.3.3. Emotional Control
28.3.4. Problem-Solving and Responsible Decision-Making

28.4. Relationship Models and Therapeutic Influence

28.4.1. Paternal Model
28.4.2. Informative Model
28.4.3. Interpretive Model
28.4.4. Deliberative Model

28.5. Tools for Emotional Support in Cancer

28.5.1. How to Speak With a Cancer Patient. Guide for Friends and Family
28.5.2. Levels of Emotional Interaction

28.6. Non-Verbal Communication in the Support Relationship
28.7. Communication in Palliative and End-of-Life Care

28.7.1. Learning to Talk About Death

28.8. Talking About Cancer With Children
28.9. Communication in People With Communication Deficits
28.10. Treatment of Cancer in the Media

28.10.1. Cancer on Social Networks

Module 29. Grief Management

29.1. Death , Culture and Society

29.1.1. Health Professionals in the Face of Death

29.2. Psychological Evaluation of Grief

29.2.1. Interview and Specific Instruments for Assessment

29.3. Common Reactions to Grief

29.3.1. Normal Grief and Complicated Grief
29.3.2. Vulnerability Factors
29.3.3. Differential Diagnosis Between Grief and Depression

29.4. Main Theoretical Models About Grief

29.4.1. Bowlby's Attachment Theory
29.4.2. Nuclear Beliefs and Meaning Reconstruction
29.4.3. Conceptual Models About the Trauma

29.5. Objectives of Intervention in Grief and Recommended Interventions

29.5.1. Facilitating the Normal Process of Grief. Prevention of Complicated Grief
29.5.2. Suggestions for Intervention Before and After the Death
29.5.3. Bereavement Psychotherapy from an Integrative Relational Model

29.6. Group Intervention in Attention to Grief

29.6.1. Psychological Intervention Grief Due to the Loss of a Child

29.7. Stages of Grief

29.7.1. Bereavement Tasks

29.8. Grief in Children
29.9. Suicide and Cancer
29.10. Psychopharmacology in Attention to Grief

Module 30. Other Psychological Interventions in Specific Cancer-Related Areas

30.1. Psychological Treatment to Give Up Smoking

30.1.1. Myths About Tobacco
30.1.2. Analysis of Smoking Behavior. Physical and Psychological Dependence
30.1.3. Program Structure. Sessions and Methodology
30.1.4. Abstinence and Prevention of Relapse

30.2. Early Detection of Cancer

30.2.1. Screening Tests (Mammography, FOBT, Cytology, etc.)
30.2.2. Anticipatory Anxiety and Difficulties in Participation
30.2.3. Oncologic Genetic Counseling

30.3. Mutual of Self-Help Groups
30.4. Psycho-Educational Groups for Family Members and Patients

30.4.1. Topics to Approach and Work Methodology
30.4.2. Inclusion and Exclusion Criteria

30.5. Psychological Intervention in Cancer Survivors. The Return to “Normality”
30.6. Control of Secondary Effects in Cancer Patients

30.6.1. Pain control
30.6.2. Against Fatigue and Sleep
30.6.3. Sexuality Control
30.6.4. Cognitive Alterations. Chemobrain Effect

30.7. Preparation and Intervention for Hospitalization and Surgery
30.8. Psychological Preparation for Other Medical Treatment (Chemotherapy, Radiotherapy, etc.)
30.9. Psychological Intervention in Bone Marrow Transplants (BMT)

30.10. Strategies for Training Volunteers in Cancer Patient Care
30.10.1. The Volunteer Interview. Assignment and Matching of the Volunteer to Each Profile
30.10.2. Specific Education of the Volunteer. Tutoring and Monitoring

Module 31. Research in Cancer

31.1. World Declaration for Cancer Research
31.2. Methodology of Cancer Research

31.2.1. Cancer Prevention Area
31.2.2. Cancer Treatment Area

31.3. Common Errors in Psych-Oncology Research
31.4. Steps to Follow to Carry Out Psycho-Oncology Research
31.5. Epidemiological Research Into Cancer
31.6. Biomedical Research

31.6.1. Participation in Clinical Trials in Cancer
31.6.2. Doubts, Risks and Benefits
31.6.3. Distribution of Clinical Trials Per Type of Cancer

31.7. Main Advances in Research

31.7.1. Priority Areas of Research in Psycho-Oncology
31.7.2. Priority Areas of Research in Palliative Care
31.7.3. New Lines of Research

31.8. Lines of Research from Social Work
31.9. Publications on Psycho-Oncology and Palliative Care in Scientific Journals
31.9.1. Writing of Scientific Articles

Module 32. Ethical Aspects in Psycho-Oncology and Psychology of Palliative Care

32.1. Telling the Patient the Truth or Not. Managing the Bearable Truth
32.2. Cancer and Ethics: A Complex Interaction

32.2.1. Principled Bioethics
32.2.2. Personalistic Bioethics
32.2.3. Double Effect Principle

32.3. Anthropological Basis

32.3.1. The Experience of Fragility
32.3.2. The Experience of Suffering
32.3.3. The Person as Wounded Healer

32.4. Rights of the Cancer Patient

32.4.1. Patient Autonomy Law
32.4.2. Informed consent
32.4.3. GDPR and Confidentiality of Medical History

32.5. Ethical Duties of Health Care Workers Caring for Cancer Patients
32.6. Death with Dignity

32.6.1. Assisted Suicide and Euthanasia
32.6.2. Adequacy or Limitation of Treatment, Refusal of Treatment, Sedation, Therapeutic Obstinacy

32.7. Participation of the Patient in Their Process of Illness, Treatment and Decision Making

32.7.1. Moral Dialogue

32.8. Humanization in the Care of Cancer Patients

32.8.1. Quality and Warmth

32.9. Ethical Care Committees and Clinical Research
32.10. Inequalities and Cancer Equity

32.10.1. Current Situation in Palliative Care

The program offers a selection of complementary readings, including scientific articles, reviews and clinical guidelines, which complement and expand the theoretical contents of the program”