A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Prognosis research and risk of bias. | LitMetric

Prognosis research and risk of bias.

Intern Emerg Med

Radiology Section, DIBIMED. University of Palermo, Via del Vespro 129, 90127, Palermo, Italy.

Published: March 2016

The interest in prognosis research has been steadily growing during the past few decades because of its impact on clinical decision making. However, since the methodology of prognosis research is still incompletely defined, the quality of published prognosis studies is largely unsatisfactory. Seven major domain for risk of bias in prognosis research have been identified, including study participation, attrition, selection of candidate predictors, outcome definition, confounding factors, analysis, and interpretation of results. The methodology for performing prognostic studies is currently aimed at avoiding such potential biases. Amongst methodologic requirements in prognosis research, the following should be considered most relevant: beforehand publication of the study protocol including the full statistical plan; inclusion of patients at a similar point along the course of the disease; rationale and biological plausibility of candidate predictors; complete information; control of overfitting and underfitting; adequate data handling and analysis; publication of the original data. Validation and analysis of the impact that prediction models have on patient management, are key steps for translation of prognosis research into clinical practice. Finally, transparent reporting of prognostic studies is essential for assessing reliability, applicability and generalizability of study results, and recommendations are now available for this aim.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11739-016-1404-zDOI Listing

Publication Analysis

Top Keywords

risk bias
8
candidate predictors
8
prognostic studies
8
prognosis
7
prognosis risk
4
bias interest
4
interest prognosis
4
prognosis steadily
4
steadily growing
4
growing decades
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!