Background Rare cystic lung diseases are increasingly recognised due the wider application of CT scanning making cystic lung disease management a growing part of respiratory care. Cystic lung diseases tend to have extrapulmonary features that can both be diagnostic but also require surveillance and treatment in their own right. As some of these diseases now have specific treatments, making a precise diagnosis is crucial. While Langerhans cell histiocytosis, Birt-Hogg-Dubé syndrome, lymphoid interstitial pneumonia and lymphangioleiomyomatosis are becoming relatively well-known diseases to respiratory physicians, a targeted and thorough workup improves diagnostic accuracy and may suggest other ultrarare diseases such as light chain deposition disease, cystic pulmonary amyloidosis, low-grade metastatic neoplasms or infections. In many cases, diagnostic information is overlooked leaving uncertainty over the disease course and treatments.

Aims This position statement from the Rare Disease Collaborative Network for cystic lung diseases will review how clinical, radiological and physiological features can be used to differentiate between these diseases.

Narrative We highlight that in many cases a multidisciplinary diagnosis can be made without the need for lung biopsy and discuss where tissue sampling is necessary when non-invasive methods leave diagnostic doubt. We suggest an initial workup focusing on points in the history which identify key disease features, underlying systemic and familial diseases and a clinical examination to search for connective tissue disease and features of genetic causes of lung cysts. All patients should have a CT of the thorax and abdomen to characterise the pattern and burden of lung cysts and extrapulmonary features and also spirometry, gas transfer and a 6 min walk test. Discussion with a rare cystic lung disease centre is suggested before a surgical biopsy is undertaken.

Conclusions We suggest that this focused workup should be performed in all people with multiple lung cysts and would streamline referral pathways, help guide early treatment, management decisions, improve patient experience and reduce overall care costs. It could also potentially catalyse a national research database to describe these less well-understood and unidentified diseases, categorise disease phenotypes and outcomes, potentially leading to better prognostic data and generating a stronger platform to understand specific disease biology.