Identifying Data 2021/22
Subject (*) Survival Analysis and Diagnostic Tests Code 6538623033
Study programme
Mestrado Universitario en Asistencia e Investigación Sanitaria (plan 2012)
Descriptors Cycle Period Year Type Credits
Official Master's Degree 2nd four-month period
 First Optional 3
Language
Spanish
Galician
Teaching method Non-attendance
Prerequisites
Department Ciencias da Saúde
Matemáticas
Coordinador
Pértega Díaz, Sonia
 E-mail
s.pertega@udc.es
Lecturers
Jacome Pumar, Maria Amalia
Pértega Díaz, Sonia
 E-mail
maria.amalia.jacome@udc.es
s.pertega@udc.es
Web
General description Esta materia consta de dous bloques diferenciados: Análise de Supervivencia (2 ETCs) e Probas diagnósticas (1 ECT). A finalidade común é establecer os elementos metodolóxicos que necesita o/a estudante para deseñar, levar a cabo e comprender os estudos clínico-epidemiolóxicos no campo das Ciencias da Saúde que impliquen análises de supervivencia ou a avaliación de probas diagnósticas.
Contingency plan MODIFICACIÓN NOS CONTIDOS
- Non se realizarán cambios
METODOLOXÍAS:
Mantéñense todas as metodoloxías propostas, que se seguirán aplicando de modo non presencial na súa totalidade a través de Teams e o Campus Virtual
MECANISMOS DE ATENCIÓN PERSONALIZADA Ao ALUMNADO
- Correo electrónico: Diariamente. De uso para facer consultas e solicitar titorías virtuais.
- Campus virtual: Diariamente.
- Teams
MODIFICACIÓNS NA EVALUCIÓN Mantense o sistema de avaliación establecido na guía docente

MODIFICACIÓNS DA BIBLIOGRAFÍA Ou WEBGRAFÍA Non se realizarán cambios.

Study programme competencies
Code Study programme competences
A1 Capacidade para elixir e aplicar as metodoloxías de investigación mais adecuadas á investigación proposta.
A4 Obter un substrato teórico suficiente para comprender o entorno clínico de aplicación das técnicas de investigación.
A5 Adquirir o coñecemento da realidade investigadora nun ámbito concreto das ciencias da saúde.
B1 Capacidade para aplicar o método científico na planificación e o desenvolvemento da investigación sanitaria.
B2 Fluidez e propiedade na comunicación científica oral e escrita.
B3 Compromiso pola calidade do desenvolvemento da actividade investigadora.
B4 Capacidade de análise e de síntese.
B5 Habilidade para manexar distintas fontes de información.
B6 Capacidade para traballar de forma colaborativa en equipos multi e interdisciplinar.
B7 Capacidade de establecer unha relación de empatía cos suxeitos implicados no desenvolvemento da actividade investigadora.
C1 Expresarse correctamente, tanto de forma oral coma escrita, nas linguas oficiais da comunidade autónoma.
C3 Utilizar as ferramentas básicas das tecnoloxías da información e as comunicacións (TIC) necesarias para o exercicio da súa profesión e para a aprendizaxe ao longo da súa vida.
C8 Valorar a importancia que ten a investigación, a innovación e o desenvolvemento tecnolóxico no avance socioeconómico e cultural da sociedade.

Learning aims
Learning outcomes Study programme competences
Skills to know and apply specific analysis tools to analyze the validity and reliability of the results of diagnostic tests in clinical practice. AR1
AR4
AR5
 BC1
BC2
BC3
BC4
BC5
BC6
BC7
 CC1
CC3
CC8
Skills to use the correct statistical procedures in a clinical research study. AR1
AR4
AR5
 BC1
BC2
BC3
BC4
BC5
BC6
BC7
 CC1
CC3
CC8

Contents
Topic Sub-topic
BLOCK 1. Survival Analysis 1.1. Introduction: types of censoring, main functions of interest.
1.2. Estimation of the survival curve: Kaplan-Meier estimator, important parametric models.
1.3. Comparison of survival curves
1.4. The proportional hazards model: Cox regression model.
1.5. The competing risk model.
BLOCK 2. Diagnostic test
 2.1. Validity and reliability of a diagnostic test: sensitivity, specificity, predictive values, likelihood ratios.
2.2. Clinical implementation of Bayes's Theorem.
2.3. ROC curves and the area under the ROC curve.
PRACTICAL CONTENT 1. Choice of the appropriate technique for data analysis, application of methods with statistical software, and interpretation of results.
2. Application of epidemiological software for the analysis of the validity and reliability of diagnostic tests.
3. Interpretation of results in the evaluation of diagnostic tests

Planning
Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
Online forum A1 A4 A5 B1 B2 B3 B4 B5 B6 B7 C1 C3 C8 0 1 1
ICT practicals A1 A5 B1 B3 B4 B5 B6 C3 0 15 15
Problem solving A1 A5 B1 B2 B3 B4 B5 B6 C8 C3 0 12 12
Supervised projects A1 A5 B1 B2 B3 B4 B5 B6 B7 C1 C3 C8 0 15 15
Guest lecture / keynote speech A1 A4 A5 B1 B2 B3 B4 B5 B6 B7 C1 C3 C8 0 24 24
Multiple-choice questions A1 A4 A5 B1 B2 B3 B4 B5 B6 B7 C1 C3 C8 0 1 1
Case study A1 A5 B1 B2 B3 B4 B5 B6 B7 C1 C3 C8 0 7 7
 
Personalized attention 0 0
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies Description
Online forum Espazo de discusión informal destinado aos estudantes para o tratamento dun tema ou problema, que se desenvolverá a través dun contorno virtual de aprendizaxe mediante ferramentas de comunicación asíncrona (foro).
ICT practicals Actividades prácticas que consistirán na aplicación dos contidos teóricos da materia mediante a utilización das tecnoloxías da información e as comunicacións. Empregarase software específico para a realización de estudos bioestatísticos ou epidemiolóxicos.
Problem solving Plantexarase a resolución de situacións prácticas concretas, a partir dos coñecementos traballados na materia
Supervised projects Traballos onde se reflicta o dominio teórico-metodolóxico da materia. Os traballos solicitaranse en formato virtual e soporte informático.
Guest lecture / keynote speech Estudio dirixido a través de material multimedia, baseado na exposición dos coñecementos teóricos da materia apoiandose no uso de medios audiovisuais
Multiple-choice questions Cuestionarios de preguntas tipo test e/ou preguntas curtas co propósito de controlar a evolución na materia
Case study Exposición dunha situación específica que suscita un problema que ten que ser comprendido, valorado e resolto por os/as alumnos/as. Plantexaranse problemas concretos en relación cos contidos da materia que describan unha situación real e describirase o proceso de resolución.

Personalized attention
Methodologies
Case study
Online forum
ICT practicals
Problem solving
Supervised projects
Description
The personalized attention related to these methodologies aims to guide students in the study of the subject and in the realization of the proposed practical works.

The follow-up will be done individually or in small groups, telematically, through email, the Virtual Campus or Teams.

Assessment
Methodologies Competencies Description Qualification
Multiple-choice questions A1 A4 A5 B1 B2 B3 B4 B5 B6 B7 C1 C3 C8 Multiple choice and short answer questions to assess the progress for each unit of the subject. 30
Problem solving A1 A5 B1 B2 B3 B4 B5 B6 C8 C3 Concrete practical situations, that will have to be solved using the contents introduced in the subject 30
Supervised projects A1 A5 B1 B2 B3 B4 B5 B6 B7 C1 C3 C8 Application of several statistical techniques to practical cases. 40
 
Assessment comments

Assessment system 

The subject is divided into two blocks: Block 1 (corresponding to Unit 1. Survival analysis) and Block 2 (corresponding to Unit  2. Diagnostic tests). Both blocks are independent, that is, one block's qualification is not affected by the other block's qualification. 

To pass the subject, it is necessary to pass both blocks separately. In that case, the final score will be the weighted sum of each block's qualification. In case of failing at least one block, the final score will be the minimum between the weighted sum of each block's qualification and the score 4.5

The final mark will be "ABSENT" (NP) only in the case the student carried out none of the assessment activities.

Concerning students of previous academic courses, the different former marks will not be kept in the current academic course.

Block I (Unit 1. Survival Analysis)

The highest score is 6.5 (out of 10), which comes from:

  • Continuous evaluation (2.5 out of 10), consisting of solving problems and multiple-choice questions to be answered online individually. 
  • A supervised project (4 out of 10), which includes the application of several statistical techniques to practical cases. It can be individual or in groups of 2-3 people.


Block II (Unit 2. Diagnostic test)

The highest score is 3.5 (out of 10), which comes from:

  • Continuous evaluation (1.75 out of 10), consisting of solving problems and/or multiple-choice questions related to the contents, to be answered online individually. 
  • Multiple-choice questions (1.75 out of 10), related to the contents, to be answered online individually. 
This assessment system will be applied in both the first and second call.

December call 

The regulation in the " Assessment, review and complaint regulation of degrees and master studies of the UDC ", article 19, shall apply. 

High honors qualification (MH) 

Students whose final qualification exceeds 9 may be eligible for honors. The teachers of the subject may consider additional criteria in the results obtained by the students in any of the training actions programmed in the teaching guide. 

Fraud 

Fraud in tests or evaluation activities will directly involve the implementation of the current rules in the Assessment, review and complaint regulation of the UDC and the  Student Statute of the UDC

All these remarks are applied to the
part-time students and/or with academic exemption.

Sources of information
Basic Hosmer, D.W. y Lemeshow, S. (1999). Applied Survival Analysis: Regression Modeling of Time to Event Data.. N.Y.: John Wiley & Sons, Inc.
López de Ullibarri Galparsoro I, Píta Fernández, S. (1998). Curvas ROC. CAD ATEN PRIMARIA 1998; 5 (4): 229-235.
Collet D (2015). Modelling survival data in medical research. London: Chapman & Hall;
Pita Fernández, S., Pértega Díaz, S. (2003). Pruebas diagnósticas: Sensibilidad y especificidad.. Cad Aten Primaria 2003; 10: 120-124.
Lee ET, Wang JW (2003). Satistical Methods for suvirval data analysis.. 3rd. ed. Belmont, CA: Lifetime learning Publications
Clark, T., Bradburn, M., Love, S. et al. (2003). Survival Analysis Part I: Basic concepts and first analyses.. Br J Cancer 89, 232–238 (2003). https://doi.org/10.1038/sj.bjc.6601118 (https://www.nature.com/artic
Pepe, M. S. (2003). The statistical evaluation of medical tests for classification and prediction. Oxford: Oxford University Press.

Complementary Pita Fernández, S (2001). Análisis de supervivencia. CAD ATEN PRIMARIA 1995; 2: 130-135. https://www.fisterra.com/mbe/investiga/supervivencia/supervivenc
SEH-LELHA (2021). Artículos de Bioestadística . https://www.seh-lelha.org/bioestadistica/
Unidade de Bioestadística Clínica del Hospital Universitario Ramón y Cajal (2021). Material docente. http://www.hrc.es/bioest/M_docente.html


Recommendations
Subjects that it is recommended to have taken before
Statistics Applied to Health Sciences/653862206
Statistical Models for Clinical Research/6538623028
Statistics Applied to Health Sciences/6538623005

Subjects that are recommended to be taken simultaneously

Subjects that continue the syllabus

Other comments

Teaching use of English: It is advisable a basic knowledge of English for reviewing the available sources of information, althought it is not mandatory. The recommended level of English is A2, as stated in the Common European Framework of Reference on Language Skills (http://cvc.cervantes.es/ensenanza/biblioteca_ele/marco/cvc_mer.pdf).


(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.