A systematic review of symptomatic diagnosis of lung cancer

Shim, Joanna, Brindle, Lucy, Simon, Michael and George, Steve (2014) A systematic review of symptomatic diagnosis of lung cancer. Family Practice, 31, 137-148. (doi:10.1093/fampra/cmt076). (PMID:24347594)

Abstract

Background. Lung cancer (LC) is often diagnosed late when curative intervention is no longer viable. However, current referral guidelines (e.g. UK National Institute for Health and Care Excellence guidelines) for suspected LC are based on a weak evidence base.
Aim. The purpose of this systematic review is to identify symptoms that are independently associated with LC and to identify the key methodological issues relating to symptomatic diagnosis research in LC.
Methods. Medline, Ovid and Cumulative Index to Nursing and Allied Health Literature were searched for the period between 1946 and 2012 using the MeSH terms ‘lung cancer’ and ‘symptom*’. Quality of each paper was assessed using Scottish Intercollegiate Guidelines Network and Consolidated Criteria for Reporting Qualitative Research Checklists and checked by a second and third reviewer.
Results. Evidence regarding the diagnostic values of most symptoms was inconclusive; haemoptysis was the only symptom consistently indicated as a predictor of LC. Generally, evidence was weakened by methodological issues such as the lack of standardized data collection (recording bias) and the lack of comparability of findings across the different studies that extend beyond the spectrum of disease. Qualitative studies indicated that patients with LC experienced symptoms months before diagnosis but did not interpret them as serious enough to seek health care. Therefore, early LC symptoms might be under-represented in primary care clinical notes.
Conclusion. Current evidence is insufficient to suggest a symptom profile for LC across the disease stages, nor can it be concluded that classical LC symptoms are predictors of LC apart from, perhaps, haemoptysis. Prospective studies are now needed that systematically record symptoms and explore their predictive values for LC diagnosis.

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Contributors

Author: Lucy Brindle

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