Literature DB >> 28483820

Lung cancer in symptomatic patients presenting in primary care: a systematic review of risk prediction tools.

Mia Schmidt-Hansen1, Sabine Berendse1, Willie Hamilton2, David R Baldwin3.   

Abstract

BACKGROUND: Lung cancer is the leading cause of cancer deaths. Around 70% of patients first presenting to specialist care have advanced disease, at which point current treatments have little effect on survival. The issue for primary care is how to recognise patients earlier and investigate appropriately. This requires an assessment of the risk of lung cancer. AIM: The aim of this study was to systematically review the existing risk prediction tools for patients presenting in primary care with symptoms that may indicate lung cancer DESIGN AND
SETTING: Systematic review of primary care data.
METHOD: Medline, PreMedline, Embase, the Cochrane Library, Web of Science, and ISI Proceedings (1980 to March 2016) were searched. The final list of included studies was agreed between two of the authors, who also appraised and summarised them.
RESULTS: Seven studies with between 1482 and 2 406 127 patients were included. The tools were all based on UK primary care data, but differed in complexity of development, number/type of variables examined/included, and outcome time frame. There were four multivariable tools with internal validation area under the curves between 0.88 and 0.92. The tools all had a number of limitations, and none have been externally validated, or had their clinical and cost impact examined.
CONCLUSION: There is insufficient evidence for the recommendation of any one of the available risk prediction tools. However, some multivariable tools showed promising discrimination. What is needed to guide clinical practice is both external validation of the existing tools and a comparative study, so that the best tools can be incorporated into clinical decision tools used in primary care. © British Journal of General Practice 2017.

Entities:  

Keywords:  clinical decision tool; diagnosis; lung neoplasms; primary health care; risk prediction; symptoms

Mesh:

Year:  2017        PMID: 28483820      PMCID: PMC5442955          DOI: 10.3399/bjgp17X690917

Source DB:  PubMed          Journal:  Br J Gen Pract        ISSN: 0960-1643            Impact factor:   5.386


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