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Acknowledgements We would like to thank all participants and funders of PICC and of the individual cohort studies. Members of PICC Steering Group: Dr. Angus D. Macleod, Dr. Carl E. Counsell, University of Aberdeen (chairperson), UK; Prof. Ole-Bjørn Tysnes, University of Bergen, Norway; Marta Camacho, Dr. Caroline Williams-Gray, University of Cambridge, UK; Dr. Rachael A. Lawson, Newcastle University, UK; Dr. Jodi Maple-Grødem, Prof. Guido Alves, Stavanger University Hospital, Norway; Prof. Lars Forgren, Umeå, Dr. David Backstrom, University, Sweden. We acknowledge the contributions of members of the individual study groups: PICNICS study: Principal investigators: Roger A. Barker, Caroline H. Williams-Gray. Study personnel: Jonathan Evans, Gemma Cummins, David P. Breen, Ruwani Wijeyekoon, Kirsten Scott, Tom Stoker, Julia Greenland, Marta Camacho, Natalie Valle Guzman, Lucy Collins, Simon Stott and Sarah Mason. ParkWest Study: ParkWest Principal investigators: Guido Alves (Norwegian Centre for Movement Disorders, Stavanger University Hospital) and Ole-Bjørn Tysnes (Haukeland University Hospital). Study personnel: Michaela Dreetz Gjerstad, Kenn Freddy Pedersen, Elin Bjelland Forsaa, Veslemøy Hamre Frantzen, Anita Laugaland, Jodi Maple-Grødem, Johannes Lange, Karen Simonsen, Eldbjørg Fiske and Ingvild Dalen, Bernd Müller, Geir Olve Skeie and Marit Renså; Wenche Telstad, Aliaksei Labusau and Jane Kastet; Ineke HogenEsch, Marianne Kjerandsen and Liv Kari Håland; Karen Herlofson, Solgunn Ongre and Siri Bruun. The PICC collaboration was funded by the Chief Scientist Office of the Scottish Government, NHS Education for Scotland, and the Academy of Medical Sciences. The PICNICS study has received funding from the Cure Parkinson's Trust, the Van Geest Foundation, the Medical Research Council (MRC) and Parkinson's UK. This work was also supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre Dementia and Neurodegeneration Theme (grant no. 146281). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. M.C. is supported by Centre for Parkinson's Plus and funded by the Evelyn Trust (proj ref 19/24). R.A.B. is supported by the Wellcome Trust Stem Cell Institute (Cambridge 203151/Z/16/Z). D.P.B. is supported by a Wellcome Clinical Research Career Development Fellowship (214571/Z/18/Z). C.H.W.G. is supported by a RCUK/UKRI Research Innovation Fellowship awarded by the MRC (MR/R007446/1) and by the Cambridge Centre for Parkinson-Plus. The Norwegian ParkWest study has been funded by the Research Council of Norway (grant number 177966) and the Western Norway Regional Health Authority (grant number 911218), and the Norwegian Parkinson's Disease Association. J.M.-G. and G.A. are supported by the Research Council of Norway (grant number 287842). R.A.L. is supported by a Senior Research Fellowship from Parkinson's UK (F-1801). ; Peer reviewed ; Publisher PDF

INTRODUCTION: Functional dependency in basic activities of daily living (ADLs) is a key outcome in Parkinson's disease (PD). We aimed to define dependency in PD, using the original and MDS versions of the Unified Parkinson's Disease Rating Scale (UPDRS). METHODS: We developed two algorithms to define dependency from items of UPDRS Part 2 and MDS-UPDRS Part 2 relating to basic ADLs (feeding, dressing, hygiene and walking, and getting out of a chair). We validated both algorithms using data from 1110 patients from six community-based PD incidence cohorts, testing concurrent validity, convergent validity, and predictive validity. RESULTS: Our optimal algorithm showed high specificity and moderate to high sensitivity versus Schwab & England <80% (specificity 95% [95% confidence interval (CI) 93-97] and sensitivity 65% [95% CI 55-73] at baseline; 88% [95% CI 85-91] and 85% [95% CI 79-97] respectively at five-years follow-up). Convergent validity was demonstrated by strong associations between dependency defined by the algorithm and cognition (MMSE), quality of life (PDQ39), and impairment (UPDRS part 3) (all p < 0.001). Algorithm-defined dependency status also predicted mortality: HR for mortality in those dependent vs independent at baseline was 1.6 (95%CI 1.2-2.1) and in those dependent vs independent at five-years' follow-up was 2.2 (1.6-3.0). DISCUSSION: We have demonstrated the concurrent validity, convergent validity, and predictive validity of a UPDRS-/MDS-UPDRS-based algorithm to define functional dependency in PD. This can be used for studying dependency in any study where UPDRS or MDS-UPDRS part 2 data have been collected. ; The PICC collaboration was funded by the Chief Scientist Office of the Scottish Government, NHS Education for Scotland, and the Academy of Medical Sciences. The CamPaIGN study has received funding from the Wellcome Trust, the Medical Research Council, the Patrick Berthoud Trust, Parkinson's UK, and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre Dementia and Neurodegeneration Theme (ref. 146281). The ICICLE-PD study was funded by Parkinson's UK (J-0802, G-1301, G-1507) and the, Lockhart Parkinson's Disease Research Fund. The research was supported by the NIHR Newcastle Biomedical Research Unit and Centre based at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University, and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre Dementia and Neurodegeneration Theme (ref. 146281). The NYPUM study was funded by Swedish Medical Research Council, Parkinson Foundation in Sweden, the Swedish Parkinson Disease Association, University of Umeå, Foundation for Clinical Neuroscience at Umeå University Hospital, Västerbotten County Council (ALF) and King Gustaf V's and Queen Victoria's foundation The Norwegian ParkWest study was funded by the Western Norway Regional Health Authority (grant No 911218), the Research Council of Norway (grant No 177966 and 287842) and the Norwegian Parkinson Research Foundation. The PICNICS study was funded by the Cure Parkinson's Trust, the Van Geest Foundation, the MRC and Parkinson's UK, and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre Dementia and Neurodegeneration Theme (ref. 146281). The PINE study was funded by Parkinson's UK, the Scottish Chief Scientist Office, NHS Grampian endowments, the BMA Doris Hillier award, RS Macdonald Trust, the BUPA Foundation and SPRING. C H Williams-Gray holds a RCUK/UKRI Research Innovation Fellowship awarded by the Medical Research Council (MR/R007446/1) and receives support from the Cambridge Centre for Parkinson-Plus.

Parkinson's disease is a complex heterogeneous disorder with urgent need for disease-modifying therapies. Progress in successful therapeutic approaches for PD will require an unprecedented level of collaboration. At a workshop hosted by Parkinson's UK and co-organized by Critical Path Institute's (C-Path) Coalition Against Major Diseases (CAMD) Consortiums, investigators from industry, academia, government and regulatory agencies agreed on the need for sharing of data to enable future success. Government agencies included EMA, FDA, NINDS/NIH and IMI (Innovative Medicines Initiative). Emerging discoveries in new biomarkers and genetic endophenotypes are contributing to our understanding of the underlying pathophysiology of PD. In parallel there is growing recognition that early intervention will be key for successful treatments aimed at disease modification. At present, there is a lack of a comprehensive understanding of disease progression and the many factors that contribute to disease progression heterogeneity. Novel therapeutic targets and trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination are required. The integration of robust clinical data sets is viewed as a powerful approach to hasten medical discovery and therapies, as is being realized across diverse disease conditions employing big data analytics for healthcare. The application of lessons learned from parallel efforts is critical to identify barriers and enable a viable path forward. A roadmap is presented for a regulatory, academic, industry and advocacy driven integrated initiative that aims to facilitate and streamline new drug trials and registrations in Parkinson's disease.

Parkinson's disease is a complex heterogeneous disorder with urgent need for disease-modifying therapies. Progress in successful therapeutic approaches for PD will require an unprecedented level of collaboration. At a workshop hosted by Parkinson's UK and co-organized by Critical Path Institute's (C-Path) Coalition Against Major Diseases (CAMD) Consortiums, investigators from industry, academia, government and regulatory agencies agreed on the need for sharing of data to enable future success. Government agencies included EMA, FDA, NINDS/NIH and IMI (Innovative Medicines Initiative). Emerging discoveries in new biomarkers and genetic endophenotypes are contributing to our understanding of the underlying pathophysiology of PD. In parallel there is growing recognition that early intervention will be key for successful treatments aimed at disease modification. At present, there is a lack of a comprehensive understanding of disease progression and the many factors that contribute to disease progression heterogeneity. Novel therapeutic targets and trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination are required. The integration of robust clinical data sets is viewed as a powerful approach to hasten medical discovery and therapies, as is being realized across diverse disease conditions employing big data analytics for healthcare. The application of lessons learned from parallel efforts is critical to identify barriers and enable a viable path forward. A roadmap is presented for a regulatory, academic, industry and advocacy driven integrated initiative that aims to facilitate and streamline new drug trials and registrations in Parkinson's disease.

Parkinson's disease is a complex heterogeneous disorder with urgent need for disease-modifying therapies. Progress in successful therapeutic approaches for PD will require an unprecedented level of collaboration. At a workshop hosted by Parkinson's UK and co-organized by Critical Path Institute's (C-Path) Coalition Against Major Diseases (CAMD) Consortiums, investigators from industry, academia, government and regulatory agencies agreed on the need for sharing of data to enable future success. Government agencies included EMA, FDA, NINDS/NIH and IMI (Innovative Medicines Initiative). Emerging discoveries in new biomarkers and genetic endophenotypes are contributing to our understanding of the underlying pathophysiology of PD. In parallel there is growing recognition that early intervention will be key for successful treatments aimed at disease modification. At present, there is a lack of a comprehensive understanding of disease progression and the many factors that contribute to disease progression heterogeneity. Novel therapeutic targets and trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination are required. The integration of robust clinical data sets is viewed as a powerful approach to hasten medical discovery and therapies, as is being realized across diverse disease conditions employing big data analytics for healthcare. The application of lessons learned from parallel efforts is critical to identify barriers and enable a viable path forward. A roadmap is presented for a regulatory, academic, industry and advocacy driven integrated initiative that aims to facilitate and streamline new drug trials and registrations in Parkinson's disease.

Parkinson's disease is a complex heterogeneous disorder with urgent need for disease-modifying therapies. Progress in successful therapeutic approaches for PD will require an unprecedented level of collaboration. At a workshop hosted by Parkinson's UK and co-organized by Critical Path Institute's (C-Path) Coalition Against Major Diseases (CAMD) Consortiums, investigators from industry, academia, government and regulatory agencies agreed on the need for sharing of data to enable future success. Government agencies included EMA, FDA, NINDS/NIH and IMI (Innovative Medicines Initiative). Emerging discoveries in new biomarkers and genetic endophenotypes are contributing to our understanding of the underlying pathophysiology of PD. In parallel there is growing recognition that early intervention will be key for successful treatments aimed at disease modification. At present, there is a lack of a comprehensive understanding of disease progression and the many factors that contribute to disease progression heterogeneity. Novel therapeutic targets and trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination are required. The integration of robust clinical data sets is viewed as a powerful approach to hasten medical discovery and therapies, as is being realized across diverse disease conditions employing big data analytics for healthcare. The application of lessons learned from parallel efforts is critical to identify barriers and enable a viable path forward. A roadmap is presented for a regulatory, academic, industry and advocacy driven integrated initiative that aims to facilitate and streamline new drug trials and registrations in Parkinson's disease.