ESMO Open最新文献

Background: Paraneoplastic inflammatory syndrome (PIS) with fever and biological inflammation is a rare but severe condition often caused by the systemic production of interleukin 6 (IL-6) by cancer cells. We report on the efficacy of tocilizumab, an anti-IL-6 receptor antibody, in 35 patients with severe PIS.

Patients and methods: All 35 patients with solid cancers (sarcomas, lung carcinoma, and breast carcinoma) diagnosed with a PIS from 2019 to 2024 treated with tocilizumab were analyzed in this single-center study (health authorities' approval R201-004-478). Patients' characteristics and clinical and biological effects of tocilizumab administration are presented.

Results: Thirty-five (97%) patients had paraneoplastic fever. The median performance status (PS) was 2 (range 1-4). Forty percent of patients had lost 10% of body weight. All had increased serum C-reactive protein (CRP) levels (median 212 mg/l), and 74% and 48% had increased polymorphonuclear leukocyte (PMN) and platelet counts, respectively. Ninety-four percent had inflammatory anemia. Tocilizumab was given once in 23 (66%) patients and more than once in 12 patients. All patients experienced resolution of paraneoplastic fever, and 11 (31%) had improved PS. CRP, PMN, and platelet count decreases were observed in 100%, 85%, and 94% of patients, respectively. Seventy-seven percent of patients had increased hemoglobin levels. CRP and inflammatory symptoms often relapsed 4-6 weeks after tocilizumab in patients receiving only one injection.

Conclusions: Tocilizumab is an efficient treatment for severe PIS providing significant improvement in clinical symptoms and biological abnormalities.

Background: Ethnic diversity in cancer clinical trials is essential to ensure that therapeutic advances are equitable and broadly applicable in multicultural societies. Yet, missing consensus on the documentation of ethnic origin, partially based on the complexity of the terminology and fear of discrimination, leads to suboptimal patient management of minority populations. Additionally, eligibility criteria, such as stringent laboratory cut-offs, often fail to account for variations across ethnic groups, potentially excluding patients without evidence-based justification.

Patients and methods: This analysis addresses this issue by investigating ethnic diversity in clinical trials that led to European Medicines Agency (EMA) and Food and Drug Administration (FDA) approvals between 2020 and 2022. Trials were identified from FDA and EMA databases, and available protocols and full-text publications were reviewed for documentation of ethnic background and eligibility criteria for organ function (bone marrow, liver, and renal). Descriptive statistics were applied to summarize the findings.

Results: Of the 56 trials analyzed, only two-thirds of primary result publications included information on ethnic origin. Caucasian and Asian groups were documented in most of those trials and also had the highest percentages of participants across trials, while other ethnic subgroups were less frequently documented and only made up a small proportion of trial participants. Eligibility criteria often set strict organ function cut-offs that did not consider variations among ethnic groups, potentially excluding minorities. The Cockcroft-Gault formula was frequently used to assess kidney function, despite its known limitations for multiethnic cohorts.

Conclusions: Ethnic homogenous participants and eligibility criteria that favor majority groups limit the applicability of findings in diverse populations, leading to inadequate patient management. While United States guidelines encourage inclusivity, similar recommendations are lacking in Europe. Thus European regulatory authorities, research organizations, and patient advocates should establish guidelines to improve ethnic diversity in cancer clinical trials, aligning research practices with the increasingly multicultural composition of European societies.

Background: Ovarian cancer (OvC) constitutes significant management challenges primarily due to its late-stage diagnosis and the development of resistance to chemotherapy. The standard treatment regimen typically includes carboplatin and paclitaxel, with the addition of poly (ADP-ribose) polymerase inhibitors for patients with high-grade serous ovarian cancer (HGSOC) harboring BRCA1/2 mutations. However, the variability in treatment responses suggests the need to investigate factors beyond BRCA1/2 mutations, such as DNA repair mechanisms and epigenetic alterations. Notably, homologous recombination repair deficiency (HRD) is observed in an additional 20% of HGSOC cases, indicating a broader spectrum of DNA repair defects. Existing commercial HRD assays have certain limitations, prompting a global effort to develop new genomic and functional tests through academic research.

Materials and methods: This study investigates, in the 187 high-grade serous and endometrioid tumors from the MITO16/MaNGO-OV-2 trial, academic HRD genomic tests in conjunction with a RAD51 immunofluorescence assay to assess functional activation of HRD. Additionally, the study incorporates analysis of microRNA-506 (miR-506) expression as a putative epigenetic effector.

Results: The RAD51 test identified HRD in 73% of the samples and genomic HRD testing in 57%, with HRD identified in 45% of samples by both tests. The significant discrepancy between the two assays emphasizes the need to refine tumor classification for HRD. A three-group genomic classification unveiled superior progression-free survival (PFS) in high- and mild-HRD tumors compared with negative-HRD tumors. High concordance between RAD51 and genomic testing in high-HRD tumors suggests a subset of 'super-HRD' tumors exhibiting superior PFS. High expression of miR-506 may be used to further refine HRD status.

Conclusions: The study underscores the complexities of HRD assessment and advocates for a combined genomic and functional approach to enhance predictive accuracy in OvC treatment responses.

Background: In a per-protocol analysis of molecularly profiled patients with treatment-refractory, end-stage cancer discussed at the National Molecular Tumor Board (NMTB), we aimed to assess the overall survival (OS) outcome of targeted treatment compared with no targeted treatment.

Materials and methods: Patients were prospectively included at a single oncological center. Whole exome and RNA sequencing (tumor-normal) were carried out, and cases were presented at the NMTB for discussion of targeted treatment. Treatment was available through a basket trial, by compassionate use or in early clinical trials.

Results: One hundred and ninety-six patients were included from 2020 to 2023. In all but three patients a driver variant was disclosed, while 42% had simultaneous affection of more than three oncogenic pathways. In 42% of patients a druggable target was identified but two-thirds did not receive the suggested treatment. The fraction of patients initiating treatment yearly rose from 8% to 22%. For patients treated (N = 30), the clinical benefit rate was 44% and median time on treatment was 3.5 months. Druggable targets were enriched in lung cancers, while patients receiving or not receiving targeted treatment had similar clinical characteristics. The median OS was longer for patients receiving targeted treatment (15 months), but similar for patients with no druggable target and suggested targeted treatment not initiated (5 and 6 months, respectively) (P = 0.004). In multivariate analysis, targeted treatment (hazard ratio 0.43, confidence interval 0.25-0.72), few metastatic sites, and adenocarcinoma histology were predictive of improved OS while alterations of the RTK/RAS pathway were prognostically unfavorable.

Conclusions: Tissue-agnostic targeted treatment based on molecular tumor profiling is possible in an increasing fraction of end-stage cancer patients. In those who receive targeted treatment, results strongly suggest a significant survival benefit.

Background: The Hormonal Bone Effects (HOBOE) study tested whether adjuvant triptorelin plus either letrozole (L) or zoledronic acid (Z) plus L (ZL) was more effective than tamoxifen (T) in premenopausal patients with hormone receptor-positive (HR+) early breast cancer (BC). Here we report the long-term follow-up analysis.

Patients and methods: HOBOE (ClinicalTrials.gov number NCT00412022) is an open-label, three-arm, randomised, phase III trial that involved 16 centres in Italy. One thousand and sixty-five premenopausal patients with HR+ early BC receiving triptorelin were randomly assigned (1 : 1 : 1) to adjuvant T, L or ZL for 5 years. Cancer recurrence, second breast or non-breast cancer and death were considered events for the intention-to-treat disease-free survival (DFS) analysis.

Results: As of 24 October 2024 at a median follow-up of 9.2 years, 199 DFS events and 79 deaths were reported. Both ZL and L improved DFS over T, with a hazard ratio (HR) of 0.58 [95% confidence interval (CI) 0.41-0.82; P = 0.002] for ZL versus T and 0.69 (95% CI 0.49-0.97, P = 0.030) for L versus T. No statistically significant difference in OS was reported (global log-rank P = 0.103). The previously reported statistically significant interaction with human epidermal growth factor receptor 2 (HER2) status was confirmed for ZL versus T comparison (P = 0.007).

Conclusion: In this updated analysis, L plus triptorelin, with or without Z, demonstrated a statistically significant DFS improvement over T plus triptorelin for the adjuvant treatment of early BC in premenopausal patients.

Background: According to the European Society for Clinical Oncology (ESMO) guidelines, the therapeutic algorithm for early-stage epithelial ovarian carcinoma (EOC) is primarily based on grading and histotype. Adjuvant chemotherapy is usually recommended for high-grade tumors and for the International Federation of Gynecology and Obstetrics (FIGO) stage IB-IC; however, overtreatment remains a concern. Conversely, patients truly at higher risk of recurrence currently lack access to additional therapeutic strategies.

Patients and methods: This study presents a descriptive analysis of early-stage EOC patients who were prospectively sequenced and stratified into high-, intermediate-, and low-risk groups based on clinicopathological features. Oncogenic alterations were identified using OncoKB and classified according to the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT) Tier I-III. The prevalence of molecular findings was first reported for each risk subgroup, followed by an analysis on the cohort of patients who experienced relapse.

Results: A total of 180 patients with FIGO stage I-II EOC were enrolled between January 2022 and December 2023; 126 patients (70%) had at least one ESCAT Tier I-III alteration (including 51% high risk, 35% intermediate risk, and 14% low risk); among them, approximately one-quarter (26%, 95% confidence interval 19% to 35%) had an ESCAT Tier I alteration. BRCA1 and BRCA2 alterations were observed in about one-quarter of patients, with BRCA2 often co-altered with POLE mutations (55%, P = 2.1 × 10^-4). Notably, almost all BRCA1 variants were found in high-risk patients. BRAF V600E mutation (ESCAT IC) was found in 2.4% of patients. PIK3CA variants were the most common Tier IIIA alterations found in 59% of patients. Among those who experienced recurrence, 60% had at least one ESCAT Tier I-III alteration, with PIK3CA mutations being the most frequent.

Conclusions: These findings highlight the potential for actionable alterations in most early-stage EOC patients and support the exploration of chemotherapy-free regimens for low- to intermediate-risk groups, as well as targeted maintenance therapy for high-risk individuals.

Background: HER2-low expression has gained clinical relevance in breast cancer (BC) due to the availability of anti-HER2 antibody-drug conjugates for patients with HER2-low metastatic BC. The well-reported instability of HER2-low status during disease evolution highlights the need to identify patients with HER2-0 primary BC who may develop a HER2-low phenotype at relapse. In response to the urgency of maximizing treatment access, we utilized artificial intelligence to predict this occurrence.

Patients and methods: We included a large multicentric retrospective cohort of patients with BC who underwent tissue resampling at relapse. The dataset was preprocessed to address relevant issues such as missing data, feature abundance, and target class imbalance. We then trained two models: one focused on explainability [Extreme Gradient Boosting (XGBoost)] and another aimed at performance (an ensemble of XGBoost and support vector machine).

Results: A total of 1200 patients were included in this study. Among 386 patients with HER2-0 primary BC and matched HER2 status at relapse, 42.5% (n = 157) converted to a HER2-low phenotype. The explainable model achieved a balanced accuracy of 58%, with a sensitivity of 53% and a specificity of 64%. The most important variables for this model were primary BC phenotype [mean Shapley value (SHAP) 0.540], primary BC histological type (SHAP 0.101), grade (SHAP 0.182), and sites of relapse (SHAP 0.008-0.213). The ensemble model had a balanced accuracy of 64%, with a sensitivity of 75% and a specificity of 53%.

Conclusions: This work represents one of the first proof-of-concept applications of machine learning models to predict a highly relevant phenomenon for drug access in modern BC oncology. Starting with an explainable model and subsequently integrating it with an ensemble approach enabled us to enhance performance while maintaining transparency, explainability, and intelligibility.

Background: Over the past two decades, the globalization of oncology clinical trials has expanded, yet significant disparities persist across countries. This study aimed to evaluate these geographical inequalities, the evolution of trial phases, and the adherence to ethical standards according to the World Bank's income group.

Materials and methods: The ClinicalTrials.gov database was searched and recorded in June 2024. We analyzed data from 87 748 oncology clinical trials conducted between 2000 and 2021, across high-income (HICs), upper-middle-income (UMICs), lower-middle-income (LMICs), and low-income countries. Key metrics included trial density, funding sources, registration timing, and trial phase distribution.

Results: The number of oncology trials increased significantly, with a mean absolute annual rise of 266.6 trials, with China currently being the leading site of early- and validation-phase trials. While HICs still present the highest trial densities, UMICs showed a notable increase in early-phase trials, reflecting a shift in research dynamics. However, despite these advances, 76.4% of countries still had no new trials initiated by 2024. Additionally, ethical practices saw improvement from 2005 to 2021 with an increase in pre-commencement registration (from 9.2% to 58%, P < 0.0001), and more validation-phase trials with a survival variable as the primary outcome (from 40% to 59.6%, P < 0.0001).

Conclusions: Despite the growth in oncology clinical trials, significant disparities in trial distribution and access remain, especially in LMICs. Continued investments in research infrastructure and adherence to ethical standards are crucial to ensure that clinical research benefits are equitably distributed, particularly in regions with the greatest need for advanced cancer therapies.

The landscape of sarcoma treatment has evolved significantly, transitioning from amputations to limb-sparing surgeries, underpinned by advancements in multidisciplinary strategies. The establishment of specialized sarcoma centers has been pivotal, though challenges in accessibility and expertise persist. This manuscript proposes the Sarcoma Hub and Spoke Model (HASM) network to address these issues, enhancing coordination and expanding access to specialized care. The HASM network centralizes complex case management at hubs while peripheral spokes manage routine diagnostics and treatments, optimizing resource use and ensuring patient-centered care. Integration with digital interoperable platforms facilitates real-time/real-world data exchange, supports multidisciplinary team meetings, and enables advanced predictive analytics such as Sarcoma Digital Twins and causal machine learning for personalized treatment. The Sarcoma Care Data Warehouse further enhances this model by aggregating comprehensive patient data, supporting quality assessment and continuous improvement. This innovative approach aims to set a new standard for sarcoma care, leveraging technology and collaborative expertise to improve outcomes globally.