bnP for pRediction of Outcome FollowIng Lung rEsection Surgery

Lung Cancer

Can BNP be used alongside current risk prediction methods to more accurately identify those at risk of breathlessness and poor quality of life following lung resection?

Lung cancer is the second most common type of cancer in the UK and the leading cause of cancer related death. Surgery to remove the tumour and the surrounding lung (lung resection) often provides the best chance of cure. Frequently, patients are smokers with related lung or heart problems increasing the risks associated with surgery. Whilst surgery for lung cancer is considered the best chance of 'cure', patients may suffer long term breathlessness, lowering quality of life. This is important; public engagement work we have performed demonstrates repeatedly that second only to being alive and cancer free exercise capacity is the main priority of post-operative patients. Prediction of breathlessness is difficult and not solely caused by lung removal but also from decreased performance of the heart. Although the surgery does not directly involve the heart, it is thought the damage is caused indirectly by the surgery and by removal of part of the lung. Current methods for predicting the risk of breathlessness after surgery are inaccurate. Some patients are refused surgery based on these methods yet may have had successful surgery. Furthermore, no specific treatment exists for patients considered to be at increased risk of breathlessness. By identifying patients at risk of breathlessness, we believe an opportunity exists to intervene. A small study we completed (a 'pilot study') suggests measuring a hormone called 'BNP' (B type- natriuretic peptide, released by the heart) will improve prediction of post-operative breathlessness. With informed consent, BNP blood levels will be measured before and after lung resection in 250 patients at 4 hospitals across the UK. We will target 100 patient recruitment at the Golden Jubilee and 50 from the other 3 centres involved. Validated questionnaires will be distributed following surgery measuring breathlessness and quality of life and returned via post at three months and at one year. Questionnaires were selected via patient and public involvement to represent what matters most to patients following surgery. This data will be integrated into current scoring systems to prove it increases identification of patients who will suffer from breathlessness and poor quality of life following surgery. Creation and testing of a risk prediction tool, or 'score', requires complex statistical techniques; we are therefore working alongside specialist biostatisticians. We hypothesise post-operative cardiac dysfunction significantly contributes to postoperative dyspnoea and a window of opportunity exists peri-operatively where targeted interventions could improve outcome. In this study, by incorporating BNP measurement into clinical risk prediction of post-operative dyspnoea in patients undergoing lung resection surgery can we improve prediction of a poor functional outcome?

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