American Journal of Clinical Oncology-Cancer Clinical Trials最新文献

Objectives: Patient navigation is a key component in achieving optimal cancer care outcomes. While a vast amount of literature suggests its clear benefits in cancer care, limited objective data exists regarding navigation metrics, specifically the number of navigator-patient contacts and time spent with patients. This study attempts to attain findings from the published literature to better understand navigation metrics to achieve optimal cancer care outcomes.

Methods: A systematic PubMed search was performed in April 2025 focusing on cancer patient navigation, with the term "patient navigation or navigator in postdiagnosis cancer care-contact metrics." Important metrics analysed were the median number of navigator-patient contacts, the median time spent per patient, the most common barriers addressed, and their respective improved outcomes. These metrics were then compared with results from the ongoing Phase I Navigator-Assisted Hypofractionation (NAVAH) trial (clinicaltrials.gov, NCT05978232).

Results: A total of 7 peer-reviewed studies met the inclusion criteria. The number of patient-navigator contacts widely ranged from 1 to 119; the average being 13.4 (∼0.3 times/mo, compared with 2 times/mo in NAVAH). The median time spent per patient varied from 40 minutes to over 10 hours (compared with 20 mins/encounter in NAVAH). The most commonly discussed topic was financial assistance, which is consistent with NAVAH findings. Improved outcomes were significantly reduced treatment interruption days and securing early specialist appointments.

Conclusions: As previously published data depicted wide variability, it highlights the need for standardized data collection and reporting practices, as such quantitative data can facilitate the evolution of patient navigation in achieving improved cancer care outcomes.

Objectives: The non-Hodgkin lymphoma class known as cutaneous T-cell lymphomas (CTCLs) is uncommon and diverse, mainly affecting the skin. The prognosis is dismal, and despite recent breakthroughs, few treatment options are available for advanced-stage disease. This narrative review outlines the current state of care for CTCLs, emphasizing innovative immunotherapies, targeted medicines, combination approaches, and epigenetic modifiers.

Methods: This paper was conducted to summarize the newer approaches to treating CTCL, with a literature search spanning PubMed, Science Direct, and Cochrane databases that identified articles reporting emerging treatments. Selected articles were categorized into sections to summarize pertinent results in a narrative report.

Results: Extracorporeal photopheresis with mogamulizumab, a monoclonal antibody targeting CCR4, has shown promise in treating skin and blood involvement while maintaining a good safety record. Additional treatments that have been highlighted include the antibody-drug combination brentuximab vedotin, which targets CD30; checkpoint inhibitors like pembrolizumab and durvalumab; and new medicines, including CD47 inhibitor TTI-621, IL-2/IL-9/IL-15 signaling inhibitor BNZ-1, pegylated interferon alpha-2a, and anti-KIR3DL2 antibody IPH4102. Even though the early clinical trial results for these novel treatments have been positive, more extensive research is required to determine the safety and efficacy of the treatments.

Conclusions: This review emphasizes the necessity for ongoing research and individualized treatment plans while highlighting the promise of these cutting-edge techniques to enhance outcomes for patients with advanced CTCL.

Objectives: Diffuse large B-cell lymphoma (DLBCL), the most common type of non-Hodgkin lymphoma, represents a highly heterogeneous cancer. Neutrophils, as the core effector cells of intrinsic immunity, play an important role in regulating the tumor microenvironment (TME) due to their functional complexity. This study aimed to assess the prognostic significance of neutrophil-related genes (NRGs) in DLBCL and their association with the TME.

Methods: Transcriptomic data and clinical information of DLBCL patients were retrieved from TCGA and GEO databases. Characterized genes were screened by LASSO, random forest, and XGBoost algorithm. A prognostic model was constructed by multivariate Cox regression analysis, and the predictive efficacy of the accuracy of the model was assessed through receiver operating characteristic (ROC) curves and Kaplan-Meier (K-M) survival analysis. Subsequently, immune cell infiltration, gene enrichment, tumor mutation burden (TMB), and drug sensitivity were analyzed across different risk groups. Finally, consensus clustering was used to identify molecular subtypes of DLBCL, and immune cell activity and immune function differences among these subtypes were compared through immune infiltration analysis.

Results: A risk stratification model established based on NRGs (TGFB2, LAMA4, GGH, F5, CD163, RasGRP4, ANXA2, S100A4, and PTEN) significantly differentiated the survival prognosis of patients in the high and low-risk groups. The low-risk group was found to have elevated immunoreactivity and a higher ESTIMATE composite score, according to immune infiltration analysis. Enrichment analysis revealed that the high risk exhibited upregulation of cell cycle regulation, DNA repair and chromosome dynamics pathways, while the low risk group exhibited extracellular matrix remodeling and activation of cytokine signaling pathways.

Conclusions: The NRG-based risk model can effectively predict the survival outcomes and immune profiles of DLBCL patients, offering a novel perspective on the link between NRGs and DLBCL.

Lactate, once viewed as a metabolic by-product of glycolysis, is now recognized as a central regulator in cancer biology. Accumulating evidence reveals that lactate actively participates in tumor progression by functioning as a metabolic fuel, signaling mediator, epigenetic modifier, and immune modulator. Tumor cells exhibit elevated glycolytic flux through the Warburg effect, producing large quantities of lactate through LDHA and exporting it through MCTs, which acidifies the tumor microenvironment and drives metabolic symbiosis, angiogenesis, and immune evasion. Lactate also stabilizes HIF-1α and activates the receptor GPR81, triggering signaling pathways that promote proliferation, invasion, and immune checkpoint expression. Epigenetically, lactate regulates histone acetylation and lactylation, modulating gene expression and supporting adaptive transcriptional programs. Immune suppression is reinforced through direct inhibition of effector T and NK cells and expansion of Tregs and MDSCs. Given its multifaceted role, lactate metabolism has emerged as a promising therapeutic target. Inhibitors of LDHA, MCT1/4, and GPR81 are under active development and show synergistic potential with immunotherapy and chemoradiotherapy. This review summarizes current advances in lactate biology and therapeutic strategies, highlighting the need for personalized approaches that consider tumor-specific lactate dependencies and signaling contexts.

Objectives: Malignant tumors of the central nervous system (CNS) are associated with high morbidity and mortality, requiring prompt and coordinated multidisciplinary care. Although adjuvant radiotherapy (RT) is a standard component of treatment that improves survival, delays in initiating RT remain common and may negatively impact patient outcomes. This study investigates patient-related factors contributing to delayed adjuvant RT in individuals with high-grade gliomas (HGGs) and brain metastases (BMs) treated at a tertiary care center in Arkansas.

Methods: Electronic medical records (EMR) were retrospectively reviewed for patients diagnosed with HGGs and BMs who sought medical treatment at the University of Arkansas for Medical Sciences (UAMS) from 2019 to 2022. Statistical analysis included evaluation of the association of sociodemographic and clinical variables with radiotherapy status, using multivariable logistic regression and survival analysis.

Results: Our sample included 219 patients diagnosed with HGGs or BMs who were treated at UAMS. Out of the 219 patients, 72.1% (n=158) patients received adjuvant RT treatment. In this group, 102 patients underwent timely RT treatment while 53 received delayed treatment. The timing of radiation was not available for 3 patients. Our analysis revealed an association between the Charlson Comorbidities Index (CCI) and RT timing status, suggesting a higher probability of receiving late RT with a higher CCI score (P=0.048). In addition, patients who received delayed RT also had a significantly longer interval between surgery and RT treatment compared with patients with timed adjuvant RT (P<0.0001 for both).

Conclusions: We found that patients with a higher CCI score suggested an increased probability of experiencing delayed RT.

Objective: Pleural effusion is a frequent and clinically significant complication in patients with non-small cell lung cancer (NSCLC), frequently causing debilitating respiratory symptoms, most notably dyspnea. The development of MPE is strongly correlated with unfavorable prognosis in NSCLC patients. This study aims to evaluate the prognostic value of multiparameter biomarkers (including CA125, CEA, CYFRA21-1, NSE, and LDH) in patients with NSCLC complicated by pleural effusion.

Methods: In this prospective cohort study, we included 119 patients diagnosed with NSCLC and pleural effusion. We systematically assessed the levels of these biomarkers in pleural effusion and their relationship with overall survival. Univariate and multivariate Cox regression analyses were used to explore the association between these biomarkers and patient prognosis.

Results: The study found that levels of CA125, CYFRA21-1, and LDH in pleural effusion were significantly correlated with overall survival, with higher levels associated with shorter survival times. In addition, as the volume of pleural effusion increased, the levels of these biomarkers also significantly rose. Multivariate Cox regression analysis indicated that age, larger pleural effusion volume, and elevated levels of CA125, CYFRA21-1, and LDH were independent risk factors for overall survival.

Conclusion: The findings of this study suggest that CA125, CYFRA21-1, and LDH in pleural effusion may be potential biomarkers for assessing prognosis in patients with NSCLC and pleural effusion. While these results offer valuable insights into their potential role in clinical practice, further validation through larger, multicenter studies is needed to confirm their prognostic significance.

Objectives: Patients with cancer may be at higher risk of heart disease from anticancer therapies. However, there is limited data on the risks of heart disease mortality after primary cancer site surgery. This study sought to evaluate the incidence, timing, and risk factors of heart disease mortality after primary cancer site surgery.

Methods: The Surveillance, Epidemiology, and End Results (SEER) database was used to perform a retrospective population-based study of cancer patients who underwent primary surgical resection from 2000 to 2020. The incidence of heart disease mortality after primary cancer site surgery was described by standardized mortality ratios (SMRs) and the timing of heart disease mortality after surgery was characterized. Risk factors were identified using Fine and Gray competing risk analysis.

Results: Among the 1,390,585 cancer patients who underwent primary surgical resection from 2000 to 2020, 178,303 (12.8%) died of heart disease. The SMR of heart disease death after surgery was 6.85 (95% CI: 6.82-6.88, P<0.001). SMRs were highest in cancers of the brain and other nervous system, esophagus, liver and intrahepatic bile duct, pancreas, and lung and bronchus. Approximately 50% of all heart disease deaths occurred within the first 5 years after surgery for all cancers. Risk factors included older age, male sex, Black race, unmarried status, and rurality.

Conclusions: The incidence of death from heart disease was significantly elevated in patients who underwent primary cancer site surgery compared with the general US population. These findings can be used to guide surgical planning and follow-up strategies.

Cancer is a major health threat in sub-Saharan Africa (SSA). Patient navigation has emerged as a strategy to address this, but the scope and impact of patient navigation for cancer care in SSA remains unclear. We aimed to comprehensively map the existing literature on patient navigation interventions for cancer care in SSA. A scoping review was conducted using a standardized 3-step search strategy. Eligible studies involved a patient navigation intervention for cancer care in SSA. Data were extracted on study, participant and navigator characteristics, intervention outcomes and implementation barriers and facilitators. Twenty-two studies describing 20 distinct interventions across 10 countries were included. Most studies were descriptive, focused on breast and cervical cancers and targeted the treatment stage of care. Navigator roles included patient education, psychosocial support, care coordination, and attenuation of patient barriers to care. Patient navigation appeared feasible, acceptable, and beneficial across a variety of study populations in this setting, but limited funding was a commonly reported barrier to maintenance. Cancer patient navigation is a promising strategy to improve cancer outcomes in SSA. Strategic investment is needed to support sustainable scale-up and maximize the impact of cancer patient navigation in the region.

Logistic models are everywhere in scientific research, including clinical and health research. However, there is no practical report on research results that will utilize many available statistical tools but mostly 1 or 2 only, for a logistic model. We introduce 6 powerful statistical tools, forest plot, AUC curve, nomogram, and decision curve analysis, as well as bootstrapping sampling and cross validation, by applying head and neck cancer data to a logistic model. We hope that these tools will make the logistic model, and accordingly our research, more comprehensive and clinically more applicable. In the 6 parts of the article, we introduce each of the 6 statistical tools (methods) with relevant figures and interpretations on key statistical concepts to show how we can improve our understanding on the logistic model and the clinical prospects behind the data. The statistical tools we present in the current special communication for reporting research or clinical trials in a logistic model, if popularized among researchers and clinicians, will make a research conclusion more comprehensive, valid and clinically applicable to other cases.

Objectives: This practice parameter was revised collaboratively by the American College of Radiology (ACR), and American Radium Society (ARS). Image-guided radiation therapy (IGRT) uses various imaging modalities to maximize the accuracy and precision of radiation treatment delivery.

Methods: This practice parameter was developed according to the process described under the heading The Process for Developing ACR Practice Parameters and Technical Standards on the ACR website ( https://www.acr.org/Clinical-Resources/Practice-Parameters-and-Technical-Standards ) by the Committee on Practice Parameters-Radiation Oncology of the ACR Commission on Radiation Oncology in collaboration with the ARS.

Results: This practice parameter for IGRT addresses qualifications and responsibilities of personnel, clinical IGRT implementation, documentation, quality control and improvement, safety, and patient education. Since the publication of the ACR-ASTRO Practice Parameter in 2019, there is now more clarity as to what criteria and parameters need to be documented in the medical record, a better appreciation of the large amount of imaging data, how to interpret such data, as well as the complex interactions of multiple systems in the implementation of IGRT.

Conclusions: This practice parameter assists practitioners in the clinical use of IGRT. IGRT should complement and be used in combination with other quality assurance processes. IGRT is a rapidly evolving field, and practitioners should have a thorough understanding of its strengths and potential limitations.