Cancer Control最新文献

Breast cancer remains the malignant tumor with the highest incidence among female patients globally, and its treatment represents a well-recognized clinical challenge. Recent studies have demonstrated that the tumor microenvironment (TME) exerts a substantial influence on breast cancer progression, whereby alterations in its internal molecular components ultimately impact disease outcomes. Key factors implicated in this process include adipokines and microRNAs (miRNAs). This review provides a detailed description of how different adipocytokines exert specific mechanistic effects on breast cancer cells. By integrating adipokines with miRNAs, the discussion explores their combined roles in the initiation and progression of breast cancer, addressing a previously unaddressed research gap in studies focusing solely on individual adipokines. Furthermore, by examining the interactions between miRNAs and signaling pathways, this analysis offers a holistic perspective on the TME network, thereby fostering new therapeutic insights for breast cancer management.

IntroductionHepatitis B and C (HBV/HCV) are bloodborne infections, with individuals who have histories of substance use and homelessness bearing a disproportionate risk. Long-standing difficulties in engaging these populations have made testing and treatment challenging. This retrospective observational study describes a community-based approach to HBV/HCV prevention and treatment, comparing the effectiveness of different engagement site types in reaching and engaging this high-need population.MethodsGRASSROOTS HEALTH was launched in 2018 to improve HBV/HCV care by providing on-site testing, HBV vaccination, treatment navigation, and adherence support across various housing and drop-in centers. Outcomes were tracked through REDCap and analyzed by engagement site.ResultsGRASSROOTS HEALTH reached nearly 2000 clients, with the greatest needs for HCV treatment in drop-in centers and HBV vaccination in low-income/permanent supportive housing. All sites demonstrated a relatively high return on effort, as evidenced by the percentage of participants needing HBV vaccination or HCV/HBV treatment.ConclusionEngaging individuals through housing and service centers effectively reached a high-need community, with findings suggesting that different engagement points may enhance outreach based on the primary focus (HCV treatment vs HBV vaccination).

IntroductionThis retrospective study compares the outcomes of right hemicolectomy (RHC) and extended right hemicolectomy (ERHC) in patients with hepatic flexure and proximal transverse colon tumors.MethodsData from 85 patients who underwent surgery for colonic adenocarcinoma between January 2015 and December 2023 were analyzed retrospectively. Patients who had hepatic flexure and proximal transverse colon tumors were included in the analysis. Patients were divided into two groups: RHC and ERHC. The primary endpoints were overall survival (OS) and disease-free survival (DFS), with secondary outcomes including postoperative complications and pathological data.ResultsThe RHC group comprised 46 patients, while the EHRC group had 39 patients. The study found no significant difference in 5-year OS (77% RHC vs 69% ERHC, P = 0.135) or 5-year DFS (87% RHC vs 81% ERHC, P = 0.388) between the two groups. Although the ERHC group had a higher number of harvested lymph nodes (27 vs 22, P = 0.022), this did not correlate with improved survival outcomes. Tumor localization was identified as a significant factor influencing OS, with hepatic flexure tumors showing better survival compared to proximal transverse colon tumors. No significant differences were observed between the groups regarding postoperative complications.ConclusionOur study suggests that while ERHC leads to a higher lymph node yield, it does not significantly improve survival outcomes compared to RHC in patients with hepatic flexure and proximal transverse colon tumors. Further research is needed to optimize surgical strategies and improve patient outcomes.

BackgroundPatients with liver cirrhosis are at a higher risk of developing non-hepatic cancers (NHC) than general population. Considering that NHC causes poor outcomes, it is necessary to explore the prevalence of NHC in such patients and identify its associated risk factors.MethodsPatients with a diagnosis of liver cirrhosis who were consecutively admitted to our hospital between January 1, 2010 and June 30, 2014 were retrospectively screened. They were divided into NHC, primary liver cancer (PLC), and non-cancer groups. After adjusting for age and sex, logistic regression analyses were performed to explore the risk factors of NHC in patients with cirrhosis. Adjusted odds ratios (aORs) with their 95% confidence intervals (CIs) were calculated.ResultsOverall, 2509 patients with cirrhosis were included. Prevalence of NHC and PLC was 6.22% (156/2509) and 22.20% (557/2509), respectively. After adjusting for age and sex, the NHC group had a significantly higher proportion of history of smoking (aOR = 1.994; 95% CI = 1.231-3.231, P = 0.005), but lower proportions of history of encephalopathy (aOR = 0.344; 95% CI = 0.147- 0.804, P = 0.014) and history of heart disease (aOR = 0.300; 95% CI = 0.173-0.519, P < 0.001) as compared to the non-cancer group. Hepatitis B virus infection (aOR = 0.863; 95% CI = 0.581-1.281, P = 0.465), hepatitis C virus infection (aOR = 0.908; 95% CI = 0.503-1.642, P = 0.750), and alcohol abuse alone (aOR = 1.254; 95% CI = 0.779-2.017, P = 0.351) as the etiology of liver cirrhosis were not significantly associated with the risk of NHC.ConclusionsSmoking may be associated with a higher probability of NHC in patients with cirrhosis, but the probability of NHC may be compromised by encephalopathy or heart disease.

IntroductionCancer screening programs are pivotal in facilitating early tumor detection and reducing cancer-related mortality. However, the reliance on individual performance indicators may not offer a fully integrated perspective of screening effectiveness. This study aimed to develop a composite indicator that consolidates key screening metrics using Principal Component Analysis (PCA) to derive objective weights.MethodsData were drawn from the annual collection of breast and colorectal cancer screening activities conducted in 2023 by the eight regional health authorities (ATSs) of Lombardy, Italy. Indicators spanning structural, organizational, clinical-diagnostic, and impact dimensions were standardized and analyzed using PCA. The resulting factor loadings informed weights for computing a weighted arithmetic mean of the z-scored indicators. Robustness was evaluated through sensitivity analyses involving alternative normalization techniques. Additionally, comparisons were made against an equally weighted arithmetic mean of the same indicators.ResultsThe composite indicator identified marked geographical variations in screening performance across Lombardy's ATSs. Structural and organizational factors, particularly examination coverage and participation rates, exerted the greatest influence on overall effectiveness in both breast and colorectal screening programs. In contrast, clinical-diagnostic and impact measures, as well as invitation coverage, contributed less substantially. High correlations in the sensitivity analyses affirmed the reliability of the proposed methodology.ConclusionsAdopting a composite indicator can substantially improve the evaluation of cancer screening initiatives by integrating diverse metrics into a cohesive, objective framework. In doing so, it enables more effective resource allocation, enhances adherence strategies, and guides targeted interventions aimed at bolstering screening success.

Introduction: Total pelvic exenteration (TPE) for clinical T4b colorectal cancer (CRC) is associated with significant morbidity. Short (0-30 days)- and intermediate (31-90 days)-term temporal analysis of complication onset is not well described, yet needed, to better counsel patients considering TPE.

Methods: A retrospective cohort study of consecutive patients with primary or recurrent clinical T4b pelvic CRC undergoing open TPE between 2014 and 2023 was conducted. Clinicopathologic variables were collected for each patient. Postoperative morbidity was classified according to the Clavien-Dindo (CD) grade system and stratified by time of onset within 90 days of surgery. Pearson's Chi-square test, Fisher's Exact test, and the Mann-Whitney U test were used to compare primary vs recurrent patient groups, and logistic regression assessed predictors of postoperative morbidity. Statistical analysis was performed using R with two-sided significance set at <0.05.

Results: Twenty-seven patients were identified of which 24 (88.9%) were male with a median age of 60.4 years (interquartile range [IQR]: 56.3-70.5). Seventeen (63.0%) patients had primary disease and 10 (37.0%) had recurrent CRC. Twenty-three (85.2%) patients experienced at least one complication within 90 days of surgery, but no mortality was observed. Ten (37.0%) patients experienced a CD ≥ 3 event, of which 40% took place beyond 30 days. The most common complication overall was anemia requiring transfusion, while the most common major complication was pelvic abscess. No clinicopathologic variables analyzed were predictive of major postoperative complication within 90 days of TPE.

Conclusion: TPE for clinical T4b CRC carries a high risk of postoperative morbidity in both the short- and intermediate-term after surgery, with a significant proportion of complications occurring after 30 days. Given the magnitude of operation, an extended recovery with high risk for complications is common. Although a single-center series, this annotated postoperative complication profile may assist patients and clinicians when reviewing informed consent for TPE.

ObjectivesWhile delays in leukemia detection remain an ongoing challenge in hematologic cancer care, little is known about the factors associated with these delays. This article focuses on identifying the barriers hindering timely diagnosis of leukemia through a cohort analysis (2016-2021) of 220 Acute Myeloid Leukemia (AML), 161 Chronic Myeloid Leukemia (CML), 90 Acute Lymphocytic Leukemia (ALL), and 121 Chronic Lymphocytic Leukemia (CLL) patients in Qatar.MethodsOf the 592 patients used for the study, subsets were identified and analyzed for delay (423), risk stratification (437), and leukemia stage (282).ResultsThere was an increasing trend in leukemia cases, with 32% of patients being diagnosed in the high-risk category. Out of 423 (median delay = 28 days) patients, 45% reported delayed diagnosis (median delay = 44 days). Further analysis of the association of delayed leukemia diagnosis using the univariate $\chi$2 independence test revealed significant associations to patient referral type, and the presence of certain comorbidities and symptoms.ConclusionSignificant delays in leukemia diagnosis were identified, though the exact cause remains unclear. These delays can be attributed to factors such as patient, primary care, referral, system, and physician delays. Therefore, further investigation is imperative for improving the detection, diagnosis, and referral processes in hematologic cancers.

IntroductionEarly-onset colorectal cancer (EOCRC) patients are more likely to have advanced diagnoses across different race/ethnicity or age at diagnosis groups. Thus, we examined the relationship of racial/ethnic disparities with cancer diagnoses (tumor features and histologic types) and 5-year causes-specific survival for EOCRC across three age-at-diagnosis groups.MethodsWe conducted a retrospective cohort analysis using the 2006-2020 Surveillance, Epidemiology, and End Results (SEER) Program, using multivariable logistic and Cox proportional hazards models to examine the association of race/ethnicity and age with survival.ResultsAmong 46,956 EOCRC patients, racial minorities were diagnosed with EOCRC at age of 20-29 years while non-Hispanic White patients were more commonly diagnosed at age 40-49 years (P-value <0.001). In adjusted analysis, non-Hispanic Black (NHB) (AOR, 1.65; 95% CI, 1.24-2.18), Asian/Pacific Islander (AOR, 2.22; 95% CI, 1.60-3.08), and Hispanic (AOR, 1.56; 95% CI, 1.27-1.93) patients aged 20-29 years were more likely to be diagnosed at a late stage. These groups were also more likely to have mucinous adenocarcinoma or signet ring cell subtypes (NHB: AOR,1.46; 95% CI, 1.00-2.13; Asian/PI: AOR, 1.89; 95% CI, 1.28-2.77; Hispanic: AOR, 1.95: 95% CI, 1.48-2.59). Regardless of age groups, NHB patients were more likely to die from CRC by 34%-59% (20-29 years: AHR, 1.40; 95% CI, 1.11-1.76; 30-39 years: AHR, 1.59; 95% CI, 1.42-1.77; 40-49 years: AHR, 1.34; 95% CI, 1.26-1.41).ConclusionPrioritizing prevention strategies and enhancing access to screening for racial minorities and the 20-29 age group is warranted.

Militaristic language is pervasive in cancer discourse across media, fundraising, politics, healthcare, and science, despite longstanding critiques from both civilian and military perspectives. Critics argue that framing cancer as a war or battle can lead to feelings of shame and inadequacy, particularly for those with metastatic cancer. This language often diverts focus from prevention and early detection strategies, complicating public perception and understanding of cancer. Two distinct research gaps related to the use of militaristic language in cancer discourse remain unaddressed: the role of dual-use technologies and the perspectives of individuals with wartime experience. Dual-use technologies, initially developed for military applications, have significantly advanced cancer diagnosis and treatment. Yet, their historical and ethical implications are largely absent from public discourse and scientific literature. Awareness of the complex role that dual-use technologies play in cancer diagnostics and treatment, as well as in other societal areas, could influence the prevalence of militaristic language used to describe challenges like cancer, drugs, poverty, and other civil issues. Secondly, studies have not examined opinions on the use of militaristic language among individuals with firsthand wartime experience, - such as civilian victims, military personnel, veterans, pacifists, and aid workers - compared to those without such experience. Both of these omissions may skew findings and overlook diverse perceptions. Addressing these research gaps could foster a more respectful public cancer discourse that takes into account the experiences of affected individuals. This commentary expands on existing critiques, urging professionals to adopt nuanced and inclusive language for cancer and other peaceful topics. Militaristic language is outdated, ethically questionable, and should not be used in science, healthcare, politics, fundraising, or other public contexts.

IntroductionCombined with the characteristics of adenocarcinoma and squamous cell carcinoma, lung adenosquamous carcinoma (ASC) is an uncommon histological subtype of lung cancer with more aggressive biological behavior. This study aimed to quantify the 90-day mortality rate in patients with ASC, identify associated features, and develop a predictive machine learning model.MethodsThis retrospective study obtained data from the Surveillance, Epidemiology, and End Results (SEER) program database, covering the period from 2000 to 2018. Through univariate logistic regression and Lasso analyses, significant prognostic features were determined. We developed predictive models using XGBoost, logistic regression, and AJCC staging algorithms, assessing their performance via metrics such as the Area Under the Receiver Operating Characteristic Curve (AUC), Decision Curve Analysis (DCA), Kolmogorov-Smirnov (KS) statistic, and calibration plots. Restricted Cubic Splines (RCS) were employed to assess potential non-linear relationships between continuous features and survival outcomes.ResultsOur analysis of 2820 eligible patients identified 6 clinical features significantly affecting outcomes. The XGBoost model exhibited exceptional discriminatory power, with AUC scores of 0.97 in the training set and 0.84 in the validation set, surpassing other models in all datasets according to AUC, KS score, DCA, and calibration analyses. RCS analysis showed a non-linear association between tumor size and prognosis, with a cutoff size of 44 mm. Moreover, we integrated the model into a web-based platform to enhance its accessibility.ConclusionsWe present a novel machine learning model, supported by an easily accessible web-based platform, to guide personalized clinical decision-making and optimize treatment strategies for patients with ASC.