Natural language processing for patient selection in phase I/II oncology clinical trials

Purpose Early discontinuation affects over one-third of patients enrolled in early-phase oncology clinical trials. Early discontinuation is deleterious both for the patient and for the study, by inflating its duration and associated costs. We aimed at predicting the successful screening and dose-limiting toxicity period completion (SSD) from automatic analysis of consultation reports. Materials and methods We retrieved the consultation reports of patients included in phase I and/or phase II oncology trials for any tumor type at Gustave Roussy, France. We designed a pre-processing pipeline that transformed free-text into numerical vectors and gathered them into semantic clusters. These document-based semantic vectors were then fed into a machine learning model that we trained to output a binary prediction of SSD status. Results Between September, 2012 and July, 2020, 56,924 consultation reports were used to build the dictionary, and 1,858 phase I/II inclusion reports were used to train (75%), validate (15%) and test (15%) a Random Forest model. Pre-processing could efficiently cluster words with semantic proximity. On the unseen test cohort of 264 consultation reports, the performances of the model reached: F1 score 0.80, recall 0.81 and AUC 0.88. Using this model, we could have reduced the screen fail rate (including DLT period) from 39.8% to 12.8% (RR=0.322, 95%CI[0.209-0.498], p<0.0001) within the test cohort. Most important semantic clusters for predictions comprised words related to hematological malignancies, anatomo-pathological features and laboratory and imaging interpretation. Conclusion Machine learning with semantic conservation is a promising tool to assist physicians in selecting patients prone to achieve SSD in early-phase oncology clinical trials. ### Competing Interest Statement LV reports personal fees from Adaptherapy, non-personal fees from Pierre-Fabre and Servier, grants from Bristol-Myers Squibb, all outside the submitted work. As part of the Drug Development Department (DITEP) = Principal/sub-Investigator of Clinical Trials for Abbvie, Adaptimmune, Aduro Biotech, Agios Pharmaceuticals, Amgen, Argen-X Bvba, Arno Therapeutics, Astex Pharmaceuticals, Astra Zeneca Ab, Aveo, Basilea Pharmaceutica International Ltd, Bayer Healthcare Ag, Bbb Technologies Bv, Beigene, Blueprint Medicines, Boehringer Ingelheim, Boston Pharmaceuticals, Bristol Myers Squibb, Ca, Celgene Corporation, Chugai Pharmaceutical Co, Clovis Oncology, Cullinan-Apollo, Daiichi Sankyo, Debiopharm, Eisai, Eisai Limited, Eli Lilly, Exelixis, Faron Pharmaceuticals Ltd, Forma Tharapeutics, Gamamabs, Genentech, Glaxosmithkline, H3 Biomedicine, Hoffmann La Roche Ag, Imcheck Therapeutics, Innate Pharma, Institut De Recherche Pierre Fabre, Iris Servier, Janssen Cilag, Janssen Research Foundation, Kura Oncology, Kyowa Kirin Pharm. Dev, Lilly France, Loxo Oncology, Lytix Biopharma As, Medimmune, Menarini Ricerche, Merck Sharp & Dohme Chibret, Merrimack Pharmaceuticals, Merus, Millennium Pharmaceuticals, Molecular Partners Ag, Nanobiotix, Nektar Therapeutics, Novartis Pharma, Octimet Oncology Nv, Oncoethix, Oncopeptides, Orion Pharma, Ose Pharma, Pfizer, Pharma Mar, Pierre Fabre, Medicament, Roche, Sanofi Aventis, Seattle Genetics, Sotio A.S, Syros Pharmaceuticals, Taiho Pharma, Tesaro, Xencor Research Grants from Astrazeneca, BMS, Boehringer Ingelheim, Janssen Cilag, Merck, Novartis, Onxeo, Pfizer, Roche, Sanofi Non-financial support (drug supplied) from Astrazeneca, Bayer, BMS, Boringher Ingelheim, Medimmune, Merck, NH TherAGuiX, Onxeo, Pfizer, Roche ### Funding Statement No funding dedicate to the study to declare. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval was given by the Medical Direction of Clinical Research at Gustave Roussy, represented by Pr Fabrice BARLESI and by the French Scientific Commission for Therapeutic Trials represeted by it President Pr Axel LE CESNE. Approval has been given at Villejuif, on Janurary 18th 2021, under the number : 2021-06 Opinion of the internal committee: The retrospective observational study entitled Natural language processing for patient selection in phase I/II oncology clinical trials submitted by Dr. Loic VERLINGUE has been reviewed and approved by the Scientific Commission of Gustave Roussy on 18/01/2021, which did not reveal any element contrary to medical ethics. Pr A. LE CESNE President C.S.E.T. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Our data is based on personal medical information with risk of identification. We are not allowed to publically disclose it. [https://github.com/DITEP/NLP\_for\_ScreenFail_prediction][1] [1]: https://github.com/DITEP/NLP_for_ScreenFail_prediction