Collaborative and privacy-enhancing workflows on a clinical data warehouse: an example developing natural language processing pipelines to detect medical conditions.

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.

Disentangling the reasons why older adults do not readily participate in cancer trials: a socio-epidemiological mixed methods approach.

BACKGROUND: Few studies of the under-representation of older adults in cancer clinical trials (CTs) have encompassed the entire pathway from a trial being available in a cancer centre to the patient's invitation to participate and then agreement or refusal to participate. OBJECTIVES: The study's primary objective was to evaluate CT non-invitation and refusal rates. The secondary objectives were to identify factors associated with non-invitation and refusal and to assess experiences of CT participation from the patients' and professionals' perspectives. METHODS: Here, we used mixed methods and a socio-epidemiological approach to analyse reasons for the non-participation of eligible older patients with a solid cancer in cancer CTs in France. RESULTS: We found that non-invitation and low CT participation are mainly related to the patients' sociodemographic characteristics and living conditions (such as social isolation, being single, divorced or widowed, not having children and the absence of close family members) and the healthcare professionals' perceptions of insufficient informal support or a high homecare requirement. CONCLUSION: Our results suggest that efforts to increase fair inclusion and the participation of older adults in CTs should target the physician-patient relationship, the medical profession and hospital funding, rather than the patient alone.

Impact of the Sars-Cov-2 outbreak on the initial clinical presentation of new solid cancer diagnoses: a systematic review and meta-analysis.

BACKGROUND: The COVID-19 pandemic might have delayed cancer diagnosis and management. The aim of this systematic review was to compare the initial tumor stage of new cancer diagnoses before and after the pandemic. METHODS: We systematically reviewed articles that compared the tumor stage of new solid cancer diagnoses before and after the initial pandemic waves. We conducted a random-effects meta-analysis to compare the rate of metastatic tumors and the distribution of stages at diagnosis. Subgroup analyses were performed by primary tumor site and by country. RESULTS: From 2,013 studies published between January 2020 and April 2022, we included 58 studies with 109,996 patients. The rate of metastatic tumors was higher after the COVID-19 outbreak than before (pooled OR: 1.29 (95% CI, 1.06-1.57), I2: 89% (95% CI, 86-91)). For specific cancers, common ORs reached statistical significance for breast (OR: 1.51 (95% CI 1.07-2.12)) and gynecologic (OR: 1.51 (95% CI 1.04-2.18)) cancers, but not for other cancer types. According to countries, common OR (95% CI) reached statistical significance only for Italy: 1.55 (1.01-2.39) and Spain:1.14 (1.02-1.29). Rates were comparable for stage I-II versus III-IV in studies for which that information was available, and for stages I-II versus stage III in studies that did not include metastatic patients. CONCLUSIONS: Despite inter-study heterogeneity, our meta-analysis showed a higher rate of metastatic tumors at diagnosis after the pandemic. The burden of social distancing policies might explain those results, as patients may have delayed seeking care.

Pharmacology of Tyrosine Kinase Inhibitors: Implications for Patients with Kidney Diseases.

Tyrosine kinase inhibitors (TKI) have introduced a significant advancement in cancer management. These compounds are administered orally, and their absorption holds a pivotal role in determining their variable efficacy. They exhibit extensive distribution within the body, binding strongly to both plasma and tissue proteins. Often reliant on efflux and influx transporters, TKI undergo primary metabolism by intestinal and hepatic cytochrome P450 enzymes, with nonkidney clearance being predominant. Owing to their limited therapeutic window, many TKI display considerable intraindividual and interindividual variability. This review offers a comprehensive analysis of the clinical pharmacokinetics of TKI, detailing their interactions with drug transporters and metabolic enzymes, while discussing potential clinical implications. The prevalence of kidney conditions, such as AKI and CKD, among patients with cancer is explored in their effect on TKI pharmacokinetics. Finally, the potential nephrotoxicity associated with TKI is also examined.

Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma.

Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed features of both, causing diagnostic uncertainty and difficulty in determining proper management. Here, we perform a comprehensive deep learning-based phenotyping of multiple cohorts of patients. We show that deep learning can reproduce the diagnosis of HCC vs. CCA with a high performance. We analyze a series of 405 cHCC-CCA patients and demonstrate that the model can reclassify the tumors as HCC or ICCA, and that the predictions are consistent with clinical outcomes, genetic alterations and in situ spatial gene expression profiling. This type of approach could improve treatment decisions and ultimately clinical outcome for patients with rare and biphenotypic cancers such as cHCC-CCA.

Development of a natural language processing model for deriving breast cancer quality indicators : A cross-sectional, multicenter study.

OBJECTIVES: Medico-administrative data are promising to automate the calculation of Healthcare Quality and Safety Indicators. Nevertheless, not all relevant indicators can be calculated with this data alone. Our feasibility study objective is to analyze 1) the availability of data sources; 2) the availability of each indicator elementary variables, and 3) to apply natural language processing to automatically retrieve such information. METHOD: We performed a multicenter cross-sectional observational feasibility study on the clinical data warehouse of Assistance Publique - Hôpitaux de Paris (AP-HP). We studied the management of breast cancer patients treated at AP-HP between January 2019 and June 2021, and the quality indicators published by the European Society of Breast Cancer Specialist, using claims data from the Programme de Médicalisation du Système d'Information (PMSI) and pathology reports. For each indicator, we calculated the number (%) of patients for whom all necessary data sources were available, and the number (%) of patients for whom all elementary variables were available in the sources, and for whom the related HQSI was computable. To extract useful data from the free text reports, we developed and validated dedicated rule-based algorithms, whose performance metrics were assessed with recall, precision, and f1-score. RESULTS: Out of 5785 female patients diagnosed with a breast cancer (60.9 years, IQR [50.0-71.9]), 5,147 (89.0%) had procedures related to breast cancer recorded in the PMSI, and 3732 (72.5%) had at least one surgery. Out of the 34 key indicators, 9 could be calculated with the PMSI alone, and 6 others became so using the data from pathology reports. Ten elementary variables were needed to calculate the 6 indicators combining the PMSI and pathology reports. The necessary sources were available for 58.8% to 94.6% of patients, depending on the indicators. The extraction algorithms developed had an average accuracy of 76.5% (min-max [32.7%-93.3%]), an average precision of 77.7% [10.0%-97.4%] and an average sensitivity of 71.6% [2.8% to 100.0%]. Once these algorithms applied, the variables needed to calculate the indicators were extracted for 2% to 88% of patients, depending on the indicators. DISCUSSION: The availability of medical reports in the electronic health records, of the elementary variables within the reports, and the performance of the extraction algorithms limit the population for which the indicators can be calculated. CONCLUSIONS: The automated calculation of quality indicators from electronic health records is a prospect that comes up against many practical obstacles.

Cancer mortality and competing causes of death in older adults with cancer: A prospective, multicentre cohort study (ELCAPA-19).

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.

Impact of the COVID-19 pandemic on clinical presentation, treatments, and outcomes of new breast cancer patients: A retrospective multicenter cohort study.

BACKGROUND: The SARS CoV-2 pandemic disrupted healthcare systems. We compared the cancer stage for new breast cancers (BCs) before and during the pandemic. METHODS: We performed a retrospective multicenter cohort study on the data warehouse of Greater Paris University Hospitals (AP-HP). We identified all female patients newly referred with a BC in 2019 and 2020. We assessed the timeline of their care trajectories, initial tumor stage, and treatment received: BC resection, exclusive systemic therapy, exclusive radiation therapy, or exclusive best supportive care (BSC). We calculated patients' 1-year overall survival (OS) and compared indicators in 2019 and 2020. RESULTS: In 2019 and 2020, 2055 and 1988, new BC patients underwent cancer treatment, and during the two lockdowns, the BC diagnoses varied by -18% and by +23% compared to 2019. De novo metastatic tumors (15% and 15%, p = 0.95), pTNM and ypTNM distributions of 1332 cases with upfront resection and of 296 cases with neoadjuvant therapy did not differ (p = 0.37, p = 0.3). The median times from first multidisciplinary meeting and from diagnosis to treatment of 19 days (interquartile 11-39 days) and 35 days (interquartile 22-65 days) did not differ. Access to plastic surgery (15% and 17%, p = 0.08) and to treatment categories did not vary: tumor resection (73% and 72%), exclusive systemic therapy (13% and 14%), exclusive radiation therapy (9% and 9%), exclusive BSC (5% and 5%) (p = 0.8). Among resected patients, the neoadjuvant therapy rate was lower in 2019 (16%) versus 2020 (20%) (p = 0.02). One-year OS rates were 99.3% versus 98.9% (HR = 0.96; 95% CI, 0.77-1.2), 72.6% versus 76.6% (HR = 1.28; 95% CI, 0.95-1.72), 96.6% versus 97.8% (HR = 1.09; 95% CI, 0.61-1.94), and 15.5% versus 15.1% (HR = 0.99; 95% CI, 0.72-1.37), in the treatment groups. CONCLUSIONS: Despite a decrease in the number of new BCs, there was no tumor stage shift, and OS did not vary.

No changes in clinical presentation, treatment strategies and survival of pancreatic cancer cases during the SARS-COV-2 outbreak: A retrospective multicenter cohort study on real-world data.

The SARS-COV-2 pandemic disrupted healthcare systems. We assessed its impact on the presentation, care trajectories and outcomes of new pancreatic cancers (PCs) in the Paris area. We performed a retrospective multicenter cohort study on the data warehouse of Greater Paris University Hospitals (AP-HP). We identified all patients newly referred with a PC between January 1, 2019, and June 30, 2021, and excluded endocrine tumors. Using claims data and health records, we analyzed the timeline of care trajectories, the initial tumor stage, the treatment categories: pancreatectomy, exclusive systemic therapy or exclusive best supportive care (BSC). We calculated patients' 1-year overall survival (OS) and compared indicators in 2019 and 2020 to 2021. We included 2335 patients. Referral fell by 29% during the first lockdown. The median time from biopsy and from first MDM to treatment were 25 days (16-50) and 21 days (11-40), respectively. Between 2019 and 2020 to 2021, the rate of metastatic tumors (36% vs 33%, P = .39), the pTNM distribution of the 464 cases with upfront tumor resection (P = .80), and the proportion of treatment categories did not vary: tumor resection (32% vs 33%), exclusive systemic therapy (49% vs 49%), exclusive BSC (19% vs 19%). The 1-year OS rates in 2019 vs 2020 to 2021 were 92% vs 89% (aHR = 1.42; 95% CI, 0.82-2.48), 52% vs 56% (aHR = 0.88; 95% CI, 0.73-1.08), 13% vs 10% (aHR = 1.00; 95% CI, 0.78-1.25), in the treatment categories, respectively. Despite an initial decrease in the number of new PCs, we did not observe any stage shift. OS did not vary significantly.

How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in Urologic Cancers.

PURPOSE: To compare the computability of Observational Medical Outcomes Partnership (OMOP)-based queries related to prescreening of patients using two versions of the OMOP common data model (CDM; v5.3 and v5.4) and to assess the performance of the Greater Paris University Hospital (APHP) prescreening tool. MATERIALS AND METHODS: We identified the prescreening information items being relevant for prescreening of patients with cancer. We randomly selected 15 academic and industry-sponsored urology phase I-IV clinical trials (CTs) launched at APHP between 2016 and 2021. The computability of the related prescreening criteria (PC) was defined by their translation rate in OMOP-compliant queries and by their execution rate on the APHP clinical data warehouse (CDW) containing data of 205,977 patients with cancer. The overall performance of the prescreening tool was assessed by the rate of true- and false-positive cases of three randomly selected CTs. RESULTS: We defined a list of 15 minimal information items being relevant for patients' prescreening. We identified 83 PC of the 534 eligibility criteria from the 15 CTs. We translated 33 and 62 PC in queries on the basis of OMOP CDM v5.3 and v5.4, respectively (translation rates of 40% and 75%, respectively). Of the 33 PC translated in the v5.3 of the OMOP CDM, 19 could be executed on the APHP CDW (execution rate of 58%). Of 83 PC, the computability rate on the APHP CDW reached 23%. On the basis of three CTs, we identified 17, 32, and 63 patients as being potentially eligible for inclusion in those CTs, resulting in positive predictive values of 53%, 41%, and 21%, respectively. CONCLUSION: We showed that PC could be formalized according to the OMOP CDM and that the oncology extension increased their translation rate through better representation of cancer natural history.

Why Are Data Missing in Clinical Data Warehouses? A Simulation Study of How Data Are Processed (and Can Be Lost).

In recent years, the development of clinical data warehouses (CDW) has put Electronic Health Records (EHR) data in the spotlight. More and more innovative technologies for healthcare are based on these EHR data. However, quality assessments on EHR data are fundamental to gain confidence in the performances of new technologies. The infrastructure developed to access EHR data - CDW - can affect EHR data quality but its impact is difficult to measure. We conducted a simulation on the Assistance Publique - Hôpitaux de Paris (AP-HP) infrastructure to assess how a study on breast cancer care pathways could be affected by the complexity of the data flows between the AP-HP Hospital Information System, the CDW, and the analysis platform. A model of the data flows was developed. We retraced the flows of specific data elements for a simulated cohort of 1,000 patients. We estimated that 756 [743;770] and 423 [367;483] patients had all the data elements necessary to reconstruct the care pathway in the analysis platform in the "best case" scenarios (losses affect the same patients) and in a random distribution scenario (losses affect patients at random), respectively.

Performance of a blood-based RNA signature for gemcitabine-based treatment in metastatic pancreatic adenocarcinoma.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, and chemotherapy is a key treatment for advanced PDAC. Gemcitabine chemotherapy is still an important component of treatment; however, there is no routine biomarker to predict its efficacy. Predictive tests may help clinicians to decide on the best first-line chemotherapy. Methods: This study is a confirmatory study of a blood-based RNA signature, called the GemciTest. This test measures the expression levels of nine genes using real-time polymerase chain reaction (PCR) processes. Clinical validation was carried out, through a discovery and a validation phases, on 336 patients (mean 68.7 years; range, 37-88 years) for whom blood was collected from two prospective cohorts and two tumor biobanks. These cohorts included previously untreated advanced PDAC patients who received either a gemcitabine- or fluoropyrimidine-based regimen. Results: Gemcitabine-based treated patients with a positive GemciTest (22.9%) had a significantly longer progression-free survival (PFS) {5.3 vs. 2.8 months; hazard ratio (HR) =0.53 [95% confidence interval (CI): 0.31-0.92]; P=0.023} and overall survival (OS) [10.4 vs. 4.8 months; HR =0.49 (95% CI: 0.29-0.85); P=0.0091]. On the contrary, fluoropyrimidine-based treated patients showed no significant difference in PFS and OS using this blood signature. Conclusions: The GemciTest demonstrated that a blood-based RNA signature has the potential to aid in personalized therapy for PDAC, leading to better survival rates for patients receiving a gemcitabine-based first-line treatment.

Intentional R1 resection of liver metastases: A new treatment paradigm for patients with advanced colorectal cancer based on a propensity score-Matched case-control analysis.

BACKGROUND: Clinical outcomes of colorectal cancer (CRC) patients after an incomplete microscopic (R1) resection of liver metastases may not differ from those following a microscopically margin negative (R0) resection, when the latest is not feasible because of anatomic issues. We aimed at comparing the clinical outcomes of CRC patients with an intentional R1 or with a R0 resection of liver metastases. METHODS: All patients with advanced in CRC and liver metastases consecutively treated by liver resection between February 2005 and January 2019 at in the department of Digestive and Hepatobiliary Surgery of Henri Mondor University Hospital (Créteil, France) were included in this retrospective case-control study. Overall survival (OS) and event-free survival (EFS) were compared between patients who underwent an intentional (pre-operative decision) R1 resection (iR1) to those who had a R0 resection of liver metastases. To account for confounding, comparison between the 2 groups was performed after adjustment using propensity score analysis. RESULTS: Twenty-six CRC patients treated by iR1 resection of liver metastases were compared to 98 patients treated by R0 resection. Median OS reached 39 months [95% confidence interval (CI): 25-67] and 63 months [95% CI: 52-76] in the iR1 and R0 groups, respectively. After adjustment by inverse probability of treatment weighting, patients' OS and EFS did not differ significantly between the iR1 and R0 groups (hazard ratio (HR): 1.19 [0.54-2.62] and 1.67 [0.93-3.03]), respectively. CONCLUSION: iR1 resection of liver metastases in advanced CRC patients is an acceptable therapeutic strategy, when R0 resection is not feasible.

Association between overweight, obesity, and quality of life of patients receiving an anticancer treatment for prostate cancer: a systematic literature review.

BACKGROUND: Prostate cancer (PCa) and obesity are two ever-increasing public health issues that can independently impair the quality of life (QOL) of affected patients. Our objective was to evaluate the impact of overweight and obesity on the QOL of patients with PCa receiving an anticancer treatment. METHODS: We performed a systematic review of the literature using PubMed, Embase, Cochrane Library and Web of Science databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. The search equation targeted studies that included PCa patients who had a body mass index (BMI) greater than 25 kg/m2, who were receiving anticancer therapy, and whose QOL was analyzed according to validated or non-validated scores. RESULTS: Of 759 identified articles, we selected 20 studies published between 2000 and 2019 of 12,529 patients treated for PCa, including 5549 overweight or obese patients. QOL assessment was performed using nine validated scales and two non-validated questionnaires. Of seven studies on radiotherapy, six found obesity to have a negative impact on patients' QOL (especially urinary, sexual, and bowel-related QOL). Thirteen studies assessed the QOL of patients who underwent radical prostatectomy, with a BMI > 25 kg/m2 having no observed impact. In obese patients under 65 years of age and without comorbidities, nerve-sparing surgery appeared to limit the deterioration of QOL. Four studies on brachytherapy found discordant results. One study showed greater QOL impairment in obese patients receiving first-generation hormone therapy than in those with normal or decreased BMI. No study evaluated the QOL of overweight or obese patients receiving other types of systemic treatment. CONCLUSION: Based on the published data, the level of evidence for an association between QOL and overweight or obesity in patients treated for PCa is not high. Prospective cohort studies including this type of patient population are warranted to answer this topical public health issue.

"In conferences, everyone goes 'health data is the future' ": an interview study on challenges in re-using EHR data for research in Clinical Data Warehouses.

More and more hospital Clinical Data Warehouses (CDWs) are developed to gain access to EHR data. The rapid growth of investments in CDWs suggest a real potential for innovation in healthcare. However, it is still not confirmed that CDWs will deliver on their promises as researchers working with CDWs face many challenges. To gain a better understanding of these challenges and how to overcome them, we conducted a series of semi-structured interviews with EHR data experts. In this article, we share some initial results from the ongoing interview study. Two main themes emerged from the analysis of the transcripts of the interviews: the importance of infrastructures in terms of data and how it is generated, and the difficulty to make care, clinical research, and data science work together. Finally, based on the experts' experience, several recommendations were identified when using a CDW.

Nestin as a diagnostic and prognostic marker for combined hepatocellular-cholangiocarcinoma.

BACKGROUND & AIMS: Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer (PLC) associated with a poor prognosis. Given the challenges in its identification and its clinical implications, biomarkers are critically needed. We aimed to investigate the diagnostic and prognostic value of the immunohistochemical expression of Nestin, a progenitor cell marker, in a large multicentric series of PLCs. METHODS: We collected 461 cHCC-CCA samples from 32 different clinical centers. Control cases included 368 hepatocellular carcinomas (HCCs) and 221 intrahepatic cholangiocarcinomas (iCCAs). Nestin immunohistochemistry was performed on whole tumor sections. Diagnostic and prognostic performances of Nestin expression were determined using receiver-operating characteristic curves and Cox regression modeling. RESULTS: Nestin was able to distinguish cHCC-CCA from HCC with AUCs of 0.85 and 0.86 on surgical and biopsy samples, respectively. Performance was lower for the distinction of cHCC-CCA from iCCA (AUCs of 0.59 and 0.60). Nestin, however, showed a high prognostic value, allowing identification of the subset of cHCC-CCA ("Nestin High", >30% neoplastic cells with positive staining) associated with the worst clinical outcome (shorter disease-free and overall survival) after surgical resection and liver transplantation, as well as when assessment was performed on biopsies. CONCLUSION: We show in different clinical settings that Nestin has diagnostic value and that it is a useful biomarker to identify the subset of cHCC-CCA associated with the worst clinical outcome. Nestin immunohistochemistry may be used to refine risk stratification and improve treatment allocation for patients with this highly aggressive malignancy. LAY SUMMARY: There are different types of primary liver cancers (i.e. cancers that originate in the liver). Accurately identifying a specific subtype of primary liver cancer (and determining its associated prognosis) is important as it can have a major impact on treatment allocation. Herein, we show that a protein called Nestin could be used to refine risk stratification and improve treatment allocation for patients with combined hepatocellular carcinoma, a rare but highly aggressive subtype of primary liver cancer.

Influence of the SARS-CoV-2 outbreak on management and prognosis of new lung cancer cases, a retrospective multicentre real-life cohort study.

INTRODUCTION: The SARS-CoV-2 pandemic has impacted the care of cancer patients. This study sought to assess the pandemic's impact on the clinical presentations and outcomes of newly referred patients with lung cancer from the Greater Paris area. METHODS: We retrospectively retrieved the electronic health records and administrative data of 11.4 million patients pertaining to Greater Paris University Hospital (AP-HP). We compared indicators for the 2018-2019 period to those of 2020 in regard to newly referred lung cancer cases. We assessed the initial tumour stage, the delay between the first multidisciplinary tumour board (MTB) and anticancer treatment initiation, and 6-month overall survival (OS) rates depending on the anticancer treatment, including surgery, palliative systemic treatment, and best supportive care (BSC). RESULT: Among 6240 patients with lung cancer, 2179 (35%) underwent tumour resection, 2069 (33%) systemic anticancer therapy, 775 (12%) BSC, whereas 1217 (20%) did not receive any treatment. During the first lockdown, the rate of new diagnoses decreased by 32% compared with that recorded in 2018-2019. Initial tumour stage, repartition of patients among treatment categories, and MTB-related delays remained unchanged. The 6-month OS rates of patients diagnosed in 2018-2019 who underwent tumour resection were 98% versus 97% (HR = 1.2; 95% CI: 0.7-2.0) for those diagnosed in 2020; the respective rates for patients who underwent systemic anticancer therapy were 78% versus 79% (HR = 1.0; 95% CI: 0.8-1.2); these rates were 20% versus 13% (HR = 1.3; 95% CI: 1.1-1.6) for those who received BSC. COVID-19 was associated with poorer OS rates (HR = 2.1; 95% CI: 1.6-3.0) for patients who received systemic anticancer therapy. CONCLUSIONS: The SARS-CoV-2 pandemic has not exerted any deleterious impact on 6-month OS of new lung cancer patients that underwent active anticancer therapy in Greater Paris University hospitals.

Impact of two waves of Sars-Cov2 outbreak on the number, clinical presentation, care trajectories and survival of patients newly referred for a colorectal cancer: A French multicentric cohort study from a large group of university hospitals.

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 1 January 2018 and 31 December 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 AP-HP, 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-year OS rates attributable to the infection itself rather than to its impact on hospital care delivery or tumor stage at initial presentation.