Results & OUtputs


Meso-ORIGINS Feasibilty Study

The Meso-ORIGINS feasibility study (IRAS ref 253522, NHS ref GN17ON341), a multi-centre cohort study which concluded in January 2021, demonstrated the feasibility of the Meso-ORIGINS study methods and allowed us to refine the study design for Meso-ORIGINS.
The feasibility study had retrospective and prospective elements and was conducted at 4 UK pleural disease centres (Glasgow, Oxford, Manchester and Bristol).

In the retrospective element, which involved database review at each site, Malignant Pleural Mesothelioma (MPM) evolved, following an initial diagnosis of asbestos associated benign pleural inflammation, in 42 of 257 eligible cases (16% (95%CI 12.3-21.4%)). Of these, MPM evolution was confirmed histologically by repeat biopsy in 36/257 (14% (95% CI 10.5-19.2). In the prospective element, 37 patients were recruited over 12 months at the 4 study centres, exceeding the minimum number needed to demonstrate and adequate recruitment rate (39 patients).

The feasibility study has therefore demonstrated:
a) how many participants are required for the Meso-ORIGINS study (i.e. it has helped us estimate our sample size more precisely)
b) that it should be possible to recruit enough participants in a reasonable amount of time, assuming the number of recruiting centres is scaled up appropriately
c) that potentially eligible participants would be willing to consent to the proposed methods of surveillance, and that a mixture of repeat biopsy methods will be needed.

The results of the feasibility study suggest that the Meso-ORIGINS aims and protocol are achievable and methods are acceptable to participants.

Shared Best Practice

Protocols, manuals and SOPs from Network members available to the mesothelioma research community.

Meso-ORIGINS sample handling manual

latest sample handling manual from Meso-ORIGINS featuring processing of blood, pleural fluid and biopsy methods


As the Network progresses, we will post Network outputs here.
These will include Open Access full text versions of Network publications; presentations; and seminar outputs.


Fully automated volumetric measurement of malignant pleural mesothelioma by deep learning AI: validation and comparison with modified RECIST response criteria