Objective: To develop and validate a natural language processing (NLP) pipeline that detects 18 conditions in French clinical notes, including 16 comorbidities of the Charlson index, while exploring a collaborative and privacy-enhancing workflow. Materials and Methods: The detection pipeline relied both on rule-based and machine learning algorithms, respectively, for named entity recognition and entity qualification, respectively. We used a large language model pre-trained on millions of clinical notes along with annotated clinical notes in the context of 3 cohort studies related to oncology, cardiology, and rheumatology. The overall workflow was conceived to foster collaboration between studies while respecting the privacy constraints of the data warehouse. We estimated the added values of the advanced technologies and of the collaborative setting. Results: The pipeline reached macro-averaged F1-score positive predictive value, sensitivity, and specificity of 95.7 (95%CI 94.5-96.3), 95.4 (95%CI 94.0-96.3), 96.0 (95%CI 94.0-96.7), and 99.2 (95%CI 99.0-99.4), respectively. F1-scores were superior to those observed using alternative technologies or non-collaborative settings. The models were shared through a secured registry. Conclusions: We demonstrated that a community of investigators working on a common clinical data warehouse could efficiently and securely collaborate to develop, validate and use sensitive artificial intelligence models. In particular, we provided an efficient and robust NLP pipeline that detects conditions mentioned in clinical notes.

The SARS-Cov2 may have impaired care trajectories, patient overall survival (OS), tumor stage at initial presentation for new colorectal cancer (CRC) cases. This study aimed at assessing those indicators before and after the beginning of the pandemic in France. In this retrospective cohort study, we collected prospectively the clinical data of the 11.4 million of patients referred to the Greater Paris University Hospitals (AP HP). We identified new CRC cases between January first 2018 and December 31st 2020, and compared indicators for 2018-2019 to 2020. pTNM tumor stage was extracted from postoperative pathology reports for localized colon cancer, and metastatic status was extracted from CT-scan baseline text reports. Between 2018 and 2020, 3602 and 1083 new colon and rectal cancers were referred to the APHP, respectively. The 1-year OS rates reached 94%, 93% and 76% for new CRC patients undergoing a resection of the primary tumor, in 2018-2019, in 2020 without any Sars-Cov2 infection and in 2020 with a Sars-Cov2 infection, respectively (HR 3.78, 95%CI 2.1-7.1). For patients undergoing other kind of anticancer treatment, the percentages are 64%, 66% and 27% (HR 2.1, 95%CI 1.4-3.3). Tumor stage at initial presentation, emergency level of primary tumor resection, delays between the first multidisciplinary meeting and the first anticancer treatment did not differ over time. The SARS-Cov2 pandemic has been associated with less newly diagnosed CRC patients and worse 1-yr OS rates attributable to the infection itself rather than to its impact on hospital care delivery or tumor stage at initial presentation.

Background: In older patients with cancer, comorbidities compete with cancer for cause of death. The objectives were to evaluate cancer mortality and factors associated, according to metastatic status.Methods: Between 2007 and 2014, patients with cancer aged ≥70 referred for pre‐therapeutic geriatric assessment (GA) were included through the ELCAPA prospective cohort study. The underlying cause of death was defined according to the International Classification of Diseases, 10th Revision. The World Health Organisation definition was used to categorise the cause of death as cancer versus another disease (e.g. cardiovascular disease, infectious disease, etc.) Competing risk models were used.Results: Mean (SD) age of the 1445 included patients was 80.2 (5.8) and 48% were women. Most common tumour sites were colorectal (19%), breast (17%) and urinary (15%); 773 patients (49%) had metastases. After a 34‐month median follow‐up, 706 cancer deaths were observed among 843 deaths. The 6‐month and 3‐year cancer mortality rates (95% CI) were 12% (9–15) and 34% (29–38) for non‐metastatic patients and 43% (39–47) and 79% (75–82) for metastatic patients, respectively. Dependency in activities of daily living and comorbidities were associated with 6‐month and 3‐year cancer mortality in non‐metastatic (adjusted subhazard ratio [aSHR] = 1.68 [0.99–2.85] and 1.69 [1.16–2.45]; and 1.98 [1.08–3.63] and 3.38 [1.47–7.76], respectively) and metastatic patients (aSHR = 2.81 [2.01–3.93] and 2.95 [2.14–4.07]; and 1.63 [1.18–2.25] and 2.06 [1.39–3.05], respectively). Impaired Timed‐Get‐Up‐and‐Go test was associated with 6‐month and 3‐year cancer mortality in metastatic patients (aSHR = 1.5 [1.06–2.12] and 1.38 [1.06–1.81], respectively). Obesity was negatively associated with 3‐year cancer death in non‐metastatic (aSHR = 0.53 [0.29–0.97]) and metastatic patients (aSHR = 0.71 [0.51–1.00]).Conclusions: The majority of older adults with cancer referred for pre‐therapeutic GA die from cancer. Geriatric parameters are independently associated with cancer mortality and should be considered for prognosis assessment, decision‐making and care.

Background: COVID-19 may be more frequent and more severe in cancer patients than in other individuals. Our aims were to assess the rate of COVID-19 in hospitalized cancer patients, to describe their demographic characteristics, clinical features and care trajectories, and to assess the mortality rate. Methods: This multicenter cohort study was based on the Electronic Health Records of the Assistance Publique-Hôpitaux de Paris (AP-HP). Cancer patients with a diagnosis of COVID-19 between 3 March and 19 May 2020 were included. Main outcome was all-cause mortality within 30 days of COVID-19 diagnosis. Results: A total of 29,141 cancer patients were identified and 7791 (27%) were tested for SARS-CoV-2. Of these, 1359 (17%) were COVID-19-positive and 1148 (84%) were hospitalized; 217 (19%) were admitted to an intensive care unit. The mortality rate was 33% (383 deaths). In multivariate analysis, mortality-related factors were male sex (aHR = 1.39 [95% CI: 1.07–1.81]), advanced age (78–86 y: aHR = 2.83 [95% CI: 1.78–4.51] vs. <66 y; 86–103 y: aHR = 2.61 [95% CI: 1.56–4.35] vs. 20 ng/mL (aHR = 2.20 [95% CI: 1.70–2.86]). Primary brains tumors (aHR = 2.19 [95% CI: 1.08–4.44]) and lung cancer (aHR = 1.66 [95% CI: 1.02–2.70]) were associated with higher mortality. Risk of dying was lower among patients with metabolic comorbidities (aHR = 0.65 [95% CI: 0.50–0.84]). Conclusions: In a hospital-based setting, cancer patients with COVID-19 had a high mortality rate. This mortality was mainly driven by age, sex, number of comorbidities and presence of inflammation. This is the first cohort of cancer patients in which metabolic comorbidities were associated with a better outcome.