Lupus nephritis is a life-threatening complication of systemic lupus erythematosus. The standard treatment for this condition, including corticosteroids and cyclophosphamide, results in a 70 % remission rate at 12 months, but it is also associated with significant morbidity. Rituximab, a chimeric anti-CD20 antibody, could be useful, given the central role of B cells in the pathogenesis of systemic lupus erythematosus. Case reports and retrospective series have reported that rituximab is effective for refractory lupus nephritis. However, the double-blind, placebo-controlled LUNAR trial failed to meet its end point. We studied clinical, biological, and immunological data on 17 patients who received rituximab as an induction treatment for refractory lupus nephritis at the University Hospital Center of Bordeaux. A complete treatment response was defined as a normal serum creatinine with inactive urinary sediment and 24-h urinary albumin <0.5 g and a partial response (PR) as a >50 % improvement in all of the renal parameters that were abnormal at baseline, with no deterioration in any parameter. Seventeen patients received rituximab as induction treatment for lupus nephritis refractory to standard treatment by cyclophosphamide. After a follow-up of 12 months, complete or partial renal remission was achieved in 53 % patients. Rituximab therapy resulted in a significant improvement in proteinuria and steroid dose tapering in all patients. Rituximab should be considered as a treatment option for refractory lupus glomerulonephritis.

Background Telemedicine is currently being adopted for the management of patients in routine care. However, its use remains limited in the context of clinical trials. Objective This study aimed to demonstrate the feasibility of telemonitoring and patient-reported outcomes collection in the context of clinical trials. Methods The patients who were included in an interventional oncology clinical trial were eligible. The patients were registered with a digital tool to respond to a patient-reported outcomes questionnaire (ePRO) based on CTCAE (The Common Terminology Criteria for Adverse Events, National Cancer Institute), version 5.0, personalized to their pathology and treatment. An algorithm evaluated the health status of the patient based on the reported adverse events, with a classification in 4 different states (correct, compromise, state to be monitored, or critical state). The main objective was to evaluate the feasibility of remote monitoring via a connected platform of patients included in a clinical trial. Results From July 1, 2020, to March 31, 2021, 39 patients were included. The median age was 71 years (range 41-94); 74% (n=29) were male, and 59% (n=23) had metastatic disease. Out of the 969 ePRO questionnaires completed over the course of the study, 77.0% (n=746) were classified as “correct,” 10.9% (n=106) as “compromised,” and 12.1% (n=117) as “to be monitored” or “critical.” The median response time was 7 days (IQR 7-15.5), and 76% (25/33) of the patients were compliant. Out of the 35 patients who answered a satisfaction questionnaire, 95% (n=33) were satisfied or very satisfied with the tool, and 85% (n=30) were satisfied with their relationship with the health care team. There were 5 unscheduled hospitalizations during the study period. Conclusions Remote monitoring in clinical trials is feasible, with a high level of patient participation and satisfaction. It benefits patients, but it also ensures the high quality of the trial through the early management of adverse events and better knowledge of the tolerance profile of experimental treatments. This e-technology will likely be deployed more widely in our clinical trials.

76 Background: The benefits of Electronic Patient Remote Outcomes (e-PRO) for telemonitoring are well established, allowing early detection of illnesses and continuous monitoring of patients. We have previously shown high levels of compliance of use of telemonitoring in daily care. This new PROTECTY study assesses the predictive power of patient health status in the first month of treatment on survival, evaluated with the telemonitoring platform Cureety. Methods: This prospective study was conducted at the Military Hospital Bégin on prostate cancer patients. Patients were allowed to respond to a symptomatology questionnaire based on CTCAE v.5.0, personalized to their pathology and treatment. An algorithm evaluates the health status of the patient based on the reported adverse events, with a classification into 2 different states: Good Health status (A) Poor Health status (B) In case of A, the patient received therapeutic advice to help manage each of the reported adverse events. In case of B, the patient is invited to call the hospital. For the purpose of this analysis, we collected their health status during the first month after initiation of treatment. The primary endpoint was to assess if the first month health status is a predictive factor of progression free-survival (PFS) for prostate cancer patient. The secondary endpoint was to assess if the first month health status is a predictive factor of overall survival (OS) for prostate cancer patient. Results: Sixty-one patients were enrolled between July 1st, 2020 and June 30st, 2021. The median age was 74.0 (range 58.0 – 94.0). 62% presented a metastatic stage, and the most represented cancer was mHSPC with 39,5% among metastatic patients. Overall, 2443 questionnaires were completed by the patients, 4.0% resulted in a health classification in state B. 86,9% of patient were classified in group A the first month. 13,1% of patient were classified in group B the first month. The median follow up was 12.3 months. PFS at 12 months was 89% in A group vs 60% in B group, p=0,17 OS at 12 months was 100% in A group vs 86% in B group, p=0,15. Conclusions: Our study is the first to assess the impact of tolerance treatment on survival. The initial results suggest that e-PRO assessment by the platform could help identify in the early stages the patients that require further health assessment and potential therapeutic changes. While further follow-up of more patients will be required, our study highlights the importance of e-PRO in cancer patient care.

Background: The Cancer and Aging Research Group (CARG) toxicity score is a validated tool to predict chemotherapy toxicity for older adults with cancer. However, little is known regarding the impact of the CARG-score on survival outcomes.Methods: This prospective study evaluated survival and toxicity outcomes according to a 2 x 2 table by CARG-score categories: non-high risk (score <10) vs. high risk (10) and treatment intensity: standard-intensity therapy (ST) vs. reduced-intensity therapy (RT). Patients were aged 65 years receiving first-line chemotherapy for advanced non-colorectal GI cancer for which combination chemotherapy is the standard of care. Treatment decision was made by the treating oncologist, who was blinded to the CARG-scores. We estimated overall survival (OS) and time to treatment failure (TTF), defined as the time from the start to discontinuation of first-line chemotherapy for any reason.Results: Fifty patients (median age, 71 years) enrolled and 76% had Karnofsky performance status (KPS) 80. Cancer types were pancreatic (60%), upper GI tract (28%) and biliary tract (12%). For 28 non-high-risk patients, median OS and TTF of patients treated with ST and RT was 19.7 months vs. 12.7 months (hazard ratio (HR), 0.65; 95% CI: 0.27-1.56) and 9.1 months vs 2.5 months (HR, 0.49; 95% CI: 0.19-1.31; P ¼ 0.16), respectively. Incidence of grade 3-5 adverse events (AEs) was 68% in ST group and 33% in RT group. Among 22 high risk patients, median OS and TTF of patients treated with ST and RT was 4.5 months vs. 3.9 months (HR, 1.25; 95% CI: 0.51-3.06; P ¼ 0.62) and 2.3 months vs 3.0 months (HR, 1.66; 95% CI: 0.66-4.19; P ¼ 0.28), respectively. Grade 3-5 AEs occurred in 92% of ST group and 70% of RT group. Additionally, CARGscore category was prognostic of OS and TTF (Table ).Conclusions: This study suggests that risk-adapted chemotherapy based on the CARGscore may result in better treatment outcomes for older adults with advanced noncolorectal GI cancers.Legal entity responsible for the study: The authors.

Background Immunotherapy alone or in combination has clearly improved the survival of patients with lung cancer. However, it may also be responsible for adverse events impacting these patients' quality of life. The ToxImmune study aims to identify prognostic factors that can help to predict immune‐related adverse events. Methods We included all patients aged 18 years and older who had received at least one dose of immune checkpoint inhibitors, with or without other therapy, between June 2015 and December 2020 and were diagnosed with nonsmall cell lung cancer or small‐cell lung cancer. Patients' baseline demographic characteristics, biological blood markers, and imaging by PET‐scanner were collected from electronic medical records. All adverse events (AEs) and immune‐related AEs (irAEs) were recorded (Common Terminology Criteria For Adverse Events V.5.0). Results Sixty‐four patients were included, of whom 60 (94%) presented at least one irAE. The incidence of Common Terminology Criteria for Adverse Events (CTCAE) grade 2 and grade 3–4 was 34% and 8% respectively. Female sex, Primitive Tumor Standardized Uptake Value Max (SUVmax) <5, number of metastases ≥3 and immunotherapy received after the first line were found to be significant risk factors for immune‐related adverse events. Based on the number of risk factors, the ToxImmune score predicts the risk of having a grade ≥2 adverse event (primitive tumor SUV ≥ 5 = 0 vs. primitive tumor SUV <5 = 1, number of metastases <3 = 0 vs. number of metastases ≥3 = 1 and L1 = 0 vs. L1 ≥ 1). The incidence of grade ≥2 adverse events was 20%, 55% and 90% with ToxImmune scores 0, 1 and = 2 respectively (p = .003). Median progression‐free survival (PFS) times were 19.2 months, 6.64 months and 2.63 months for ToxImmune scores 0, 1 and = 2 respectively, p = .13. Median overall survival times were 22.6 months, 16.4 months and 9.8 months for ToxImmune scores 0, 1 and ≥2 respectively, p = .24. The disease control rate (DRR) was 78% in ToxIummune score 0 group, and 50% in ToxImmune score 1 and ≥2 groups (p = .363). Conclusion The ToxImmune score, which is grounded on objective clinical parameters, indicates that cases with a high score had an advanced threat of severe adverse events. The ToxImmune score could therefore be used in clinical practice to identify patients treated for lung cancer with immunotherapy and at risk of severe AE.

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While telemedicine has been shown to improve the quality of care for cancer patients, it remains underused for older patients (OP), partly due to the assumption that OPs are unabled or unwilling to use digital tools. However, more than 50% of new cancers are diagnosed in people over 70. The ConnectElderlyPatientToDoctor study aimed to evaluate the OP compliance with the use of the digital telemonitoring platform Cureety in oncology. All cancer patients followed at the Military Hospital Bégin were eligible for the study. Patients were invited to respond to a symptomatology questionnaire personalized to their pathology and treatment. An algorithm evaluated the health status of the patient based on the reported adverse events. The population was divided into two groups, OP and younger patients (YP), based on a cut-off at 70 years. The primary endpoint was to assess the compliance of OPs with the use of the digital oncology platform Cureety, compared to YP. From July 2020 to September 2021, a total of 117 patients were included in our study. We found that 66% of the patients were compliant, with no difference between the two groups (71.2% of YP, 61.7% of OP, P = .29). In OPs, progression free survival (PFS) ratio at 6-months was 64.6% in the tolerant patients vs 23.4% in the nontolerant patients (HR = 0.1980, 95% CI = 0.04431-0.8845, P = .0339). The median PFS was 23.3 months in the tolerant group vs 3.3 months in the nontolerant group (P = .0339). The data of overall survival are immature. OPs had a clear benefit from using this platform, similar to what was observed for YP. Patients felt less isolated and felt that they benefited from personalized care with early ambulatory medical care of adverse events. We also found that the health indicators collected with the platform in the first month of treatment are predictive of the progression of the disease. This solution makes it possible to streamline and improve the care pathway of OP.

Objective To help identify homogeneous subgroups among patients with anti-polymyositis-scleroderma-antibodies (PM-Scl-Abs) positive auto-immune diseases regardless of diagnostic classifications. Methods This multicentric (four hospitals) retrospective study collected all consecutive patients (from 2011 to 2021) with positive testing for anti-PM-Scl-Abs in a context of connective tissue disease. Subgroups of patients with similar clinico-biological phenotypes were defined using unsupervised multiple correspondence analysis and hierarchical clustering analysis of the features recorded in the first year of follow-up. Results One hundred and forty-two patients with anti-PM-Scl-Abs were evaluated and 129 patients were included in the clustering analysis and divided into 3 clusters. Cluster n°1 (n = 47) included patients with frequent skin thickening, digestive involvement and interstitial lung disease (ILD) with Non Specific Interstitial Pneumonia (NSIP). They were more likely to develop progressive fibrosing ILD. Cluster n°2 (n = 36) included patients who all featured NSIP with frequent Organizing pneumonia associated pattern and mechanic’s hands. This subgroup had increased risk of relapse and ILD was characterized by a good functional outcome. Cluster n°3 (n = 46) was characterized by predominant or isolated musculoskeletal involvement and frequently matched undifferentiated connective tissue disease (UCTD) criteria. Although very frequent among Anti PM-Scl-Abs positive patients, muscle involvement was less discriminating compared with skin thickening and ILD pattern to classify patients into subgroups. Conclusion Anti-PM-Scl-Abs associated auto-immune diseases are segregated into 3 subgroups with distinct clinical phenotype and outcomes. Skin thickening and NSIP are determinant predictors in segregation of theses populations.