Xavier Durando

Background and Aims: Short peripheral catheter (SPC) insertion is crucial in nursing practice and is one of the primary routes for therapeutic administration. Despite its widespread use, this procedure can be challenging for patients with difficult venous access. The management of chronic or long‐term pathologies and their associated therapies is directly conditioned by the success or failure of venous access. A Dutch study has developed a scoring system implementing criteria to predict the risk of failure of SPC insertion. This scoring system, derived from a two‐phase study, identified clear predictive criteria for procedure success or failure, and demonstrated a direct correlation between the score and the probability of failure. This suggests the potential usefulness of implementing this system to improve initial patient assessment before SPC insertion. Methods: This is a two‐phase interventional study evaluating the impact of the modified A‐DIVA score on SPC insertion success. In the first phase, the investigator will assess practices by obtaining the modified A‐DIVA score before each SPC insertion. In the second phase, nurses will receive training to apply the modified A‐DIVA score and then will use the score before each insertion attempt. The primary outcome measure is the success rate for SPC insertion at first attempt in both groups. The DIVAPERF trial has been recruiting patients since February 2024 and recruitment is expected to end in December 2028. Results: This study will evaluate whether the implementation of modified A‐DIVA score before each SPC insertion improves first‐attempt success. Conclusion: It is hypothesized that the modified A‐DIVA score will guide nurses to adjust their approach, improving first‐attempt success rates. Trial and Protocol Registration: The DIVAPERF trial is registered with the French Medicines Agency (2023‐A01480‐45) and ClinicalTrials.gov (NCT06062199). Protocol V3.0 (02/04/2025).

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Introduction: Ovarian cancer is the eighth most common cancer among women, accounting for 4.7% of all cancer-related deaths. Objective: In this review, we aimed to describe both established and emerging, prognostic and predictive factors. Results: Some established prognostic factors are clinical, such as age, ECOG, and Body Mass Index. Histological subtype, stage and grade are also prognostic factors, and optimal surgery is one of the main factors. Furthermore, the presence of ascites at diagnosis and cancer Antigen 125 assessment could help to predict patient outcomes. Nevertheless, median survival is less than 5 years. Among the emerging factors, tumor-infiltrating lymphocytes (TILs) have a proven prognostic value, although their predictive value has not been used in routine practice. Inflammatory response marker ratios, i.e., neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios, could have a prognostic value. Circulating tumor DNA is one of the most promising prognostic and predictive factors. Concerning predictive factors, the main one is homologous recombination deficiency, which is a marker for response to PARP inhibitors and platin-based chemotherapy. The KELIM score is also used to predict chemosensitivity. To be validated in routine practice, other predictive factors require further investigation. Conclusion: Despite the poor prognosis in this pathology, some patients are still alive 10 years after diagnosis. A better understanding of this population’s characteristics could help to anticipate patient outcomes and thus adapt their management.

Purpose: Previous studies have reported the benefit of dual HER2-targeting combined to neoadjuvant chemotherapy in HER2-amplified breast cancer (HER2 + BC). Moreover, besides the cardiac toxicity following their association to Trastuzumab, anthracyclines chemotherapy may not profit all patients. The NeoTOP study was designed to evaluate the complementary action of Trastuzumab and Pertuzumab, and the relevance of an anthracycline-based regimen according to TOP2A amplification status. Methods: Open-label, multicentre, phase II study. Eligible patients were aged ≥ 18 with untreated, operable, histologically confirmed HER2 + BC. After centralized review of TOP2A status, TOP2A-amplified (TOP2A+) patients received FEC100 for 3 cycles then 3 cycles of Trastuzumab (8 mg/kg then 6 mg/kg), Pertuzumab (840 mg/kg then 420 mg/kg), and Docetaxel (75mg/m² then 100mg/m²). TOP2A-not amplified (TOP2A-) patients received 6 cycles of Docetaxel (75mg/m²) and Carboplatin (target AUC 6 mg/ml/min) plus Trastuzumab and Pertuzumab. Primary endpoint was pathological Complete Response (pCR) using Chevallier’s classification. Secondary endpoints included pCR (Sataloff), Progression-Free Survival (PFS), Overall Survival (OS), and toxicity. Results: Out of 74 patients, 41 and 33 were allocated to the TOP2A + and TOP2A- groups respectively. pCR rates (Chevallier) were 74.4% (95%CI: 58.9–85.4) vs. 71.9% (95%CI: 54.6–84.4) in the TOP2A + vs. TOP2A- groups. pCR rates (Sataloff), 5-year PFS and OS were 70.6% (95%CI: 53.8–83.2) vs. 61.5% (95%CI: 42.5–77.6), 82.4% (95%CI: 62.2–93.6) vs. 100% (95%CI: 74.1–100), and 90% (95%CI: 69.8–98.3) vs. 100% (95%CI: 74.1–100). Toxicity profile was consistent with previous reports. Conclusion: Our results showed high pCR rates with Trastuzumab and Pertuzumab associated to chemotherapy. They were similar in TOP2A + and TOP2A- groups and the current role of neoadjuvant anthracycline-based chemotherapy remains questioned. Trial registration number: NCT02339532 (registered on 14/12/14).

Background: Real-world data (RWD) related to the health status and care of cancer patients reflect the ongoing medical practice, and their analysis yields essential real-world evidence. Advanced information technologies are vital for their collection, qualification, and reuse in research projects. Methods: UNICANCER, the French federation of comprehensive cancer centres, has innovated a unique research network: Consore. This potent federated tool enables the analysis of data from millions of cancer patients across eleven French hospitals. Results: Currently operational within eleven French cancer centres, Consore employs natural language processing to structure the therapeutic management data of approximately 1.3 million cancer patients. These data originate from their electronic medical records, encompassing about 65 million medical records. Thanks to the structured data, which are harmonized within a common data model, and its federated search tool, Consore can create patient cohorts based on patient or tumor characteristics, and treatment modalities. This ability to derive larger cohorts is particularly attractive when studying rare cancers. Conclusions: Consore serves as a tremendous data mining instrument that propels French cancer centres into the big data era. With its federated technical architecture and unique shared data model, Consore facilitates compliance with regulations and acceleration of cancer research projects.

Background: Real-world data (RWD) related to the health status and care of cancer patients reflect the ongoing medical practice, and their analysis yields essential real-world evidence. Advanced information technologies are vital for their collection, qualification, and reuse in research projects. Methods: UNICANCER, the French federation of comprehensive cancer centres, has innovated a unique research network : Consore. This potent federated tool enables the analysis of data from millions of cancer patients across eleven French hospitals. Results: Currently operational within eleven French cancer centres, Consore employs natural language processing to structure the therapeutic management data of approximately 1.3 million cancer patients. This data originates from their electronic medical records, encompassing about 65 millions of medical records. Thanks to the structured data, which is harmonized within a common data model, and its federated search tool, Consore can create patient cohorts based on patient or tumor characteristics, and treatment modalities. This ability to derive larger cohorts is particularly attractive when studying rare cancers. Conclusions: Consore serves as a tremendous data mining instrument that propels French cancer centres into the big data era. With its federated technical architecture and unique shared data model, Consore facilitates compliance to regulations and acceleration of cancer research projects.