Primary care prescribing prior to lung cancer diagnosis (PPP-Lung): protocol for a systematic review

Background Lung cancer is the second most common cancer and the leading cause of cancer death worldwide. A significant reason for its high mortality is delayed diagnosis, with lung cancer typically diagnosed at an advanced stage. Previous research has shown that prescribing rates of certain medications increase in the 24 months preceding a cancer diagnosis. This suggests a potential opportunity for early diagnosis of lung cancer by the identification of high-risk patients based on the prescribing of medications associated with a subsequent lung cancer diagnosis. Our aim is to identify all prescribing events associated within an increased incidence of primary lung cancer in the subsequent 24 months. Methods We will conduct a systematic review, and, where possible, a meta-analysis, reporting the findings in accordance with the PRISMA reporting guideline. All peer-reviewed studies in the English language that quantitatively describe an association between prescribing data and lung cancer diagnosis using a control group will be eligible. Details regarding prescribing rate in the lung cancer group versus the control group will be extracted with study characteristics. Quality appraisal of studies, using ROBINS-E will be used for assessing risk of bias. For each drug studied, we will report prescribing rate ratios (PRRs) with 95% confidence intervals (CIs). A meta-analysis using a pooled estimate of PRRs, either by fixed or random-effect models, will be performed if possible. Conclusions This systematic review will summarise the evidence on drugs that, when prescribed, suggest the possibility of an as-yet-undiagnosed lung cancer. This research has the potential to impact clinical practice by informing targeted screening strategies and refining early detection protocols for this harmful disease. If achieved, this could increase the numbers of lung cancers diagnosed at an earlier stage, with consequent improvements to patients in terms of survival, treatment tolerability and quality of life.