Cancer Control最新文献

Background: Multi-cancer early detection tests (MCEDs) have the potential to identify over 50 types of cancer from a blood sample, possibly transforming cancer screening paradigms. Studies on the safety and effectiveness of MCEDs are underway, but there is a paucity of research exploring public views on MCEDs. We sought to explore public perspectives and understanding on the use of MCEDs in patient care.

Methods: We conducted a cross-sectional, qualitative study using one-on-one, semi-structured interviews. Residents of the United States aged 45-70 years old were recruited through a survey panel and purposively sampled to maximize racial diversity. Interviews explored understanding of MCEDs and perspectives on their use. Interviews were analyzed using thematic analysis with deductive coding and semi-quantification.

Results: Among 27 participants, mean age was 62 years (range 48-70) and most (63%) were non-white. Most participants had completed at least one cancer screening (89%). Participants had a positive impression of MCEDs (85%) and found the concept easy to understand (88%). They were enthusiastic about the convenience of MCEDs (30%) and thought they would improve "cancer outcomes" by looking for multiple cancers (70%) and facilitating early detection (33%). Participants emphasized the need to balance these benefits against potential harms, including inaccuracy (96%), cost (92%), test-related anxiety (56%), and lack of evidence of effectiveness (22%). Participants favored that MCEDs be delivered in primary care (93%). Participants worried that the potential benefits of MCEDs might not be equitably distributed (44%).

Conclusions: Members of the US public in this study expressed an interest in using MCEDs but had concerns regarding cost, accuracy, and potential inequitable access to the tests. Findings suggest that MCEDs that are found to be safe and effective will be acceptable to patients as a part of primary care, and underscore public interest in improving this technology.

Objective: Advanced gastric cancer (AGC) is a severe malignant tumor, and overexpression of HER2/ERBB2 may play a crucial role in its development. The purpose of this study is to investigate the overexpression of HER2/ERBB2 in gastric cancer through a meta-analysis and examine its relationship with perfusion parameters using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) technology.

Methods: We conducted an extensive literature search and collected relevant studies for the meta-analysis. We used a random-effects model and assigned weights using the "inverse variance" method. Additionally, we included 95 AGC patients diagnosed pathologically between April 2018 and October 2021. They all underwent DCE-MRI scans, and the data were subsequently analyzed using the Omni kinetic software. HER2 expression was assessed using immunohistochemistry.

Results: The meta-analysis revealed an overall odds ratio (OR) of .21 for HER2/ERBB2 overexpression in gastric cancer, with a 95% confidence interval of [.14, .30]. DCE-MRI results showed a significant association between high HER2 expression and poor tumor differentiation (P < .005). The extracellular volume fraction (Ecv) quantile, mean, relative deviation, median intensity, and difference entropy were significantly higher in the low HER2 expression group compared to the high HER2 expression group. Receiver operating characteristic (ROC) curve analysis demonstrated that the area under the curve (AUC) values of DCE-MRI radiomic parameters with significant differences were close to .7.

Conclusion: Overexpression of HER2/ERBB2 in gastric cancer is significantly associated with certain radiomic parameters of DCE-MRI, providing a valuable diagnostic tool for clinical practice. Furthermore, the meta-analysis further confirmed the critical role of HER2/ERBB2 in the development of gastric cancer.

The advent of artificial intelligence in healthcare is transforming medical research and clinical practice, with significant advancements in the areas of oncology. This commentary explores the pivotal role artificial intelligence plays in lung cancer research, offering insights into its current applications and future potential.

Objective: The clinical characteristics and prognosis of primary epithelial-myoepithelial carcinoma of salivary gland (EMC-SG) have not been defined well due to its rarity. The purpose of this study is to assess the proportion of EMC-SG among salivary gland cancers, describe the clinicopathological features and prognosis of this disease, further analyze the factors associated with EMC-SG survival, and establish individual survival-predicting models.

Methods: Data on patients diagnosed with salivary gland malignancy between 2000 and 2020 were collected from the Surveillance, Epidemiology, and End Results database. The Kaplan-Meier method and log-rank test were employed to estimate survival of EMC-SG patients. Univariable and multivariable Cox proportional hazards models were developed to determine the EMC-SG survival-associated factors. Furthermore, EMC-SG nomograms were constructed.

Results: A total of 15 212 patients with salivary gland malignancy were identified. Of these, 310 cases were diagnosed with EMC-SG, representing a prevalence of 2.03% (95%CI 1.82%-2.28%). The overall survival (OS) rates for all 310 EMC-SG patients at 2-year, 5-year, and 10-year were 92.43%, 84.85%, and 73.39%, respectively. Age, primary site, and T stage were independent prognostic factors for OS, while pathological grade and the use of surgery were independent prognostic factors for cancer-specific survival (CSS). The concordance index (C-index) for the OS- and CSS-specific nomograms was 0.72 (95%CI 0.64-0.80) and 0.77 (95%CI 0.67-0.87), respectively. The calibration curve and receiver operating characteristic analysis demonstrated that the predicted values aligned well with the actual observations. Decision curve analysis indicated the superiority of the nomograms over the traditional Tumor Node Metastasis staging system.

Conclusions: This study represents the largest cohort of EMC-SG patients used to investigate the characteristics and prognosis of this disease. EMC-SG patients often have a less aggressive course and favorable prognosis. The established nomograms provide a useful tool for clinicians to predict patient outcomes, and can assist in customizing the counseling approach for this rare disease.

Purpose: To date, only a few studies have investigated the role of molecular alterations in cancer recurrence. This exploratory study aimed to evaluate the impact of molecular alterations on the time and site of recurrence in patients with stage I-IV CRC and to identify the risk factors predicting recurrence-free survival in colon cancer.

Methods: A total of 270 patients were retrospectively included. We assessed the full RAS status using Sanger and pyrosequencing. MSI status was determined by immunohistochemical analysis. Molecular alterations were correlated with recurrence timing (early or late), recurrence patterns, and recurrence-free survival. Statistical analysis was performed using the Kaplan-Meier method and the log-rank test.

Results: Of the 270 patients, 85 (31%) experienced recurrence, among whom 53% had mutant full RAS status, 48% had KRAS mutations, and 31.4% had KRAS p. G12V mutation subtype. Compared with those with late recurrence, patients with early recurrence were significantly older (P = 0.02) and more likely to have poorly differentiated tumors, a higher rate of positive lymph nodes, KRAS mutations, and especially KRAS p. G12V mutation variant. RAS mutation status, KRAS mutations, and rare mutations are more common in patients with lung cancer recurrence. Multivariate logistic regression analysis revealed that differentiation, perineural invasion, full RAS mutation status, and KRAS codon 13 mutations were independent factors for recurrence-free survival in colon cancer.

Conclusion: In this cohort, the timing and patterns of recurrence appeared to be associated with the patient's molecular profile. KRAS codon 12 mutations were the worst predictors of recurrence-free survival at all stages in our population.

Cancer treatment optimizations select the most optimum combinations of drugs, sequencing schedules, and appropriate doses that would limit toxicity and yield an improved patient quality of life. However, these optimizations often lack an adequate consideration of cancer's near-infinite potential for evolutionary adaptation to therapeutic interventions. Adapting cancer therapy based on monitored tumor burden and clonal composition is an intuitively sound approach to the treatment of cancer as an inherently complex and adaptive system. The adaptation would be driven by clinical outcome setpoints embodying the aims to thwart therapeutic resistance and maintain a long-term management of the disease or even a cure. However, given the nonlinear, stochastic dynamics of tumor response to therapeutic interventions, adaptive therapeutic strategies may at least need a one-step-ahead prediction of tumor burden to maintain their control over tumor growth dynamics. The article explores the feasibility of adaptive cancer treatment driven by tumor state feedback assuming cell adaptive fitness to be the underlying source of phenotypic plasticity and pathway entropy as a biomarker of tumor growth trajectory. The exploration is undertaken using deterministic and stochastic models of tumor growth dynamics.

The human papillomavirus (HPV) is a typical sexually transmitted disease that affects different epithelial cells and can cause a number of health problems. HPV is mainly spread through sexual contact and is extremely contagious, even in the absence of obvious symptoms. It is linked to a number of malignancies, such as oropharyngeal, cervical, anal, vulvar, vaginal, and cutaneous as well as anogenital and cutaneous warts. Different vaccines targeting various HPV virus strains have been produced to prevent HPV infections. Vaccines can help prevent HPV-related illnesses, but they cannot cure malignancies that have already been caused by HPV. But new developments in mRNA vaccines have shown potential in combating malignancies linked to HPV. mRNA vaccines stimulate the immune system to identify and attack particular proteins present in viruses or tumour cells. The efficacy of mRNA vaccines in preventing HPV-related malignancies has been shown in preliminary experiments in mice. Additionally, in clinical trials aimed at individuals with HPV-related head and neck malignancies, personalised mRNA vaccines in combination with immune checkpoint drugs have demonstrated encouraging results. Even though mRNA vaccines have drawbacks and restrictions such as immunogenicity and instability, further research and development in this area has a great deal of promise for developing effective therapies for HPV-related malignancies.

Purpose: Metastatic pulmonary large cell neuroendocrine carcinoma (LCNEC) is an aggressive cancer with generally poor outcomes. Effective methods for predicting survival in patients with metastatic LCNEC are needed. This study aimed to identify independent survival predictors and develop nomograms for predicting survival in patients with metastatic LCNEC.

Patients and methods: We conducted a retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database, identifying patients with metastatic LCNEC diagnosed between 2010 and 2017. To find independent predictors of cancer-specific survival (CSS), we performed Cox regression analysis. A nomogram was developed to predict the 6-, 12-, and 18-month CSS rates of patients with metastatic LCNEC. The concordance index (C-index), area under the receiver operating characteristic (ROC) curves (AUC), and calibration curves were adopted with the aim of assessing whether the model can be discriminative and reliable. Decision curve analyses (DCAs) were used to assess the model's utility and benefits from a clinical perspective.

Results: This study enrolled a total of 616 patients, of whom 432 were allocated to the training cohort and 184 to the validation cohort. Age, T staging, N staging, metastatic sites, radiotherapy, and chemotherapy were identified as independent prognostic factors for patients with metastatic LCNEC based on multivariable Cox regression analysis results. The nomogram showed strong performance with C-index values of 0.733 and 0.728 for the training and validation cohorts, respectively. ROC curves indicated good predictive performance of the model, with AUC values of 0.796, 0.735, and 0.736 for predicting the 6-, 12-, and 18-month CSS rates of patients with metastatic LCNEC in the training cohort, and 0.795, 0.801, and 0.780 in the validation cohort, respectively. Calibration curves and DCAs confirmed the nomogram's reliability and clinical utility.

Conclusion: The new nomogram was developed for predicting CSS in patients with metastatic LCNEC, providing personalized risk evaluation and aiding clinical decision-making.

Background: The appearance of the new coronavirus, SARS-CoV-2, in Wuhan - China, in 2019 led to the declaration of a COVID-19 pandemic by the World Health Organization. Peru confirmed its first case on March 6, 2020, prompting a significant change in medical care.

Purpose: Our objective was to determine the impact of the COVID-19 pandemic on cancer treatment in Peru.

Methods: A retrospective analysis of hospital data from the National Institute of Neoplastic Diseases revealed substantial decreases in oncological treatments in 2020 compared to 2019.

Results: Oncological treatments involving bone marrow transplantation had a greater impact between the months of April and September, at -100% (p=0.003). However, treatments involving surgery in April (-95% [p≤0.001]), radiotherapy in May (-76% [p=0.002]) and chemotherapy in June (-71% [p≤0.001]) also showed significant impacts. Comparative analysis with international data revealed similar trends in cancer care interruptions in different countries. However, variations in the magnitude of the impact were observed, influenced by regional health policies and the severity of the pandemic.

Conclusions: The findings underscore the challenges cancer care providers face during public health crises, requiring adaptive strategies to ensure continued access to essential treatments. Addressing these challenges requires comprehensive public health responses to mitigate the impact of future crises on cancer care systems.