Cancer Control最新文献

IntroductionBrain metastases (BM) represent a common and fatal progression in small cell lung cancer (SCLC), yet prognostic tools for this population remain underdeveloped. This study aimed to establish and externally validate a machine learning-based model to predict overall survival (OS) in SCLC patients with BM.MethodsWe extracted clinical data from 2392 SCLC patients with BM from the SEER database to construct prognostic models using Cox regression, AJCC staging, and four machine learning algorithms: Random Survival Forest (RSF), Extreme Gradient Boosting (XGB), Elastic Net (Enet), and Artificial Neural Network (ANN). Key features were selected via Lasso-Cox regression. Model performance was evaluated using time-dependent AUC, calibration curves, Brier scores, precision-recall (PR) curves, and decision curve analysis (DCA). SHAP and partial dependence plots were applied for model interpretability. External validation was conducted using an independent hospital-based cohort of 85 patients, with comparability to the SEER cohort addressed through inverse probability of treatment weighting (IPTW).ResultsAmong all models, the RSF algorithm demonstrated the best overall performance. In the training cohort, it achieved AUCs of 0.738 and 0.809 for 1-year and 2-year OS, respectively. In the internal validation cohort, AUCs were 0.718 and 0.748, and in the external validation cohort, 0.686 and 0.802, respectively. The RSF model also showed favorable calibration and the lowest Brier scores across datasets. SHAP analysis ranked chemotherapy, liver metastasis, N stage, and age as the most influential prognostic features. A web-based calculator was developed to enable real-time individualized risk prediction.ConclusionsThis study presents a robust, interpretable, and externally validated RSF-based model for predicting OS in SCLC patients with BM. The model offers clinically relevant insights and is accessible via an online tool, supporting its potential integration into personalized treatment planning.

IntroductionMyelodysplastic syndromes (MDS) are clonal hematopoietic disorders characterized by ineffective hematopoiesis, cytopenia, and risk of progression to acute myeloid leukemia. Somatic mutations in RAS pathway, including NRAS, KRAS, and PTPN11, are known contributors to leukemogenesis, yet their prognostic significance in MDS remains incompletely defined. This systematic review and meta-analysis assesses the impact of RAS pathway genes mutation on survival outcomes in adult patients with MDS.MethodsPubMed, Embase, Scopus, Web of Science, and Gene Expression Omnibus were systematically searched on January 2025. This review included English-language studies involving adults with MDS that examined the impact of RAS pathway mutations on survival, including either hazard ratios or Kaplan-Meier data. Studies were excluded if they included only specific treatments, narrow subgroups, secondary MDS, or were not original research. Sixteen papers eventually met the inclusion criteria. Data extraction and quality assessment were independently performed by multiple reviewers. The methodological quality of each study was assessed using the MASTER scale. Hazard ratios were pooled using a random-effects model.ResultsSixteen retrospective cohort studies involving 7969 patients tested for RAS pathway mutations were included. KRAS mutations were associated with poorer overall survival when compared to patients without the mutation (HR 1.66, 95% CI 1.32-2.08, P < 0.001). NRAS mutations were linked to worse overall survival (HR 1.73, 95% CI 1.46-2.04, P < 0.001) and leukemia-free survival (HR 2.48, 95% CI 1.47-4.18, P < 0.001) in comparison to those without the mutation. PTPN11 mutations were also associated with decreased overall survival (HR 1.36, 95% CI 1.01-1.85, P = 0.046) compared to individuals without the mutation.ConclusionMutations in the RAS pathway, particularly NRAS, KRAS, and PTPN11, are associated with inferior survival outcomes in adult patients with MDS. These findings underscore the prognostic relevance of RAS mutations and highlight their potential utility in refining current risk stratification models such as IPSS-M, WPSS, and MDAS.

IntroductionThe influence of iodine on papillary thyroid carcinoma (PTC) remains a subject of debate. This meta-analysis was conducted to evaluate the risk association between varying levels of iodine intake and the occurrence of PTC and different subtypes of thyroid carcinoma (TC), particularly papillary thyroid microcarcinoma (PTMC).MethodsFour databases-the Cochrane Library, Embase, PubMed, and Web of Science-were systematically searched for relevant studies published up until May 30, 2024. An updated search was conducted on November 20, 2025. Literature screening and information collection were performed according to predefined eligibility criteria. The Newcastle-Ottawa Scale (NOS) was used to appraise the quality of the eligible literature. Statistical analysis was performed using Stata 17.ResultsThis meta-analysis encompassed 17 studies involving 273 651 individuals. The findings revealed a correlation between high urinary iodine concentrations and an increased risk of TC (odds ratio [OR]: 6.43, 95% confidence interval [CI]: 2.72-15.22, P < .05). The elevated risk was observed for both PTC (OR: 7.56, 95% CI: 1.6-35.78, P < .001) and PTMC (OR: 8.96, 95% CI: 5.89-13.64, P < .001). These results suggested that greater urinary iodine concentrations were associated with a higher risk of TC. However, there was no significant association between dietary iodine intake and TC risk (OR: 0.75, 95% CI: 0.37-1.52, P > .05).ConclusionThis meta-analysis demonstrated a definitive link between high urinary iodine excretion and an increased risk of TC. The relationship between dietary iodine intake and TC requires further investigation. Considering the current limitations, future large-scale, multicenter, prospective investigations are anticipated to provide further validation.

IntroductionManaging biopsy-confirmed cervical intraepithelial neoplasia grade 2 (CIN2) in women of reproductive age poses clinical challenges. Immediate treatment with large-loop excision of the transformation zone (LLETZ) is associated with a substantial risk of adverse obstetric outcomes. This study aimed to identify the risk factors for predicting CIN3+ lesions in reproductive-aged women with biopsy-diagnosed CIN2, to inform personalized management strategies that are particularly relevant to China's evolving fertility policies.MethodsThis retrospective cohort study analyzed the data from a regional cervical lesion screening database. Reproductive-aged women (<45 years) with biopsy-confirmed CIN2 who underwent subsequent LLETZ between 2016-2024 were included in the study (n=516). Pathological upgrade was defined as CIN3+ in the LLETZ specimen. Univariate and multivariate logistic regression analyses identified independent risk factors for pathological upgrade.ResultsFollowing LLETZ, 18.4% (95/516) of the women had CIN3+ lesions, indicating biopsy underestimation. HPV 16 (56.3%) and HPV 52 (27.5%) were the most prevalent genotypes in CIN3+ and CIN2- groups, respectively. Multivariable analysis identified three independent predictors: liquid-based cytology (TCT) ≥HSIL (OR = 6.308; 95% CI: 2.390-16.650; P<0.001); specific HR-HPV genotypes: HPV 16 infection (OR = 2.372; 95% CI: 1.165-4.831; P=0.017) and HPV 33 infection (OR = 3.263; 95% CI: 1.035-10.292; P=0.044); endocervical curettage (ECC) ≥CIN2 (OR = 3.067; 95% CI: 1.474-6.384; P=0.003). Age did not increase the risk of developing CIN3+ lesions.ConclusionThis risk-stratification model offers evidence-based guidance for optimizing individualized treatment decisions in clinical settings where fertility preservation is prioritized.

Comprehensive cancer rehabilitation programs that incorporate evidence-based physical activity (PA) and exercise are currently recommended as a standard component of cancer care. However, reach and access to cancer rehabilitation is fragmented due to patient-, healthcare provider-, and organizational-level barriers. Artificial intelligence (AI), including both generative AI (e.g. chatbots that use large language models) and predictive AI techniques (e.g. forecasting future outcomes), holds potential to scale cancer rehabilitation at a relatively low cost, while filling critical gaps in care. The purpose of this narrative review is to introduce the concept of AI-supported cancer rehabilitation and synthesize emerging evidence focused on PA and structured exercise interventions. We found that existing research on the role of AI to support cancer rehabilitation is in its early stages. To-date, AI has been used to support cancer rehabilitation to: 1) screen and identify patients in need of rehabilitation; 2) predict exercise training responses and outcomes; 3) enhance patient engagement and behavior change (e.g., through feedback, coaching, or conversational agents); and 4) support precision exercise prescription. Early AI-supported interventions have demonstrated modest improvements in PA levels, although evidence remains limited. We outline priority research questions and summarize key challenges relating to the ethics, equity, and implementation of AI-tools to support cancer rehabilitation. By leveraging multidisciplinary collaboration and patient-engagement, ethically and effectively designed AI-supported cancer rehabilitation tools have the potential to overcome barriers to cancer rehabilitation access and delivery, while remaining trustworthy and meaningful to end-users.

IntroductionThe aim of this study was to determine the success rate of alternative chemotherapy regimens, and related factors, in Gestational Trophoblastic Neoplasia (GTN) patients who failed first-line Methotrexate (MTX) chemotherapy at Tu Du Hospital, Vietnam.MethodsThis was a retrospective cohort study of 124 patients with post-molar GTN resistant to MTX, who were treated between January 2018 and December 2023 at Tu Du Hospital. We used the log-rank test and Cox proportional hazard model to determine factors related to failure of alternative chemotherapy.ResultsThe success rate of alternative chemotherapy was 89.52%. There were 13/124 cases requiring salvage chemotherapy; the salvage chemotherapy rate in the Act-D group was 16.67%, and in the EMA-CO group 3.44%. Based on the multivariate regression analysis model, the prognostic factors for failure of alternative chemotherapy were the number of MTX chemotherapy cycles < 4 (HR = 0.24, 95% CI = 0.07 - 0.83, p=0.024), and the alternative chemotherapy regimen being Act-D (HR = 9.51, 95% CI = 2.27 - 39.82, p=0.002). Regarding safety, EMA-CO was associated with significantly higher hematological toxicity. Grade 3-4 neutropenia and leukopenia occurred in 56.9% and 43.1% of the EMA-CO group, respectively, compared to 13.6% and 9.1% in the Act-D group (p<0.001).ConclusionThe success rate of alternative chemotherapy was 89.52%; factors including the number of MTX chemotherapy cycles and the type of alternative chemotherapy regimen being Act-D were prognostic factors for failure.

IntroductionCervical cancer (CC) is the leading cause of cancer-related deaths among women in Uganda, largely due to late diagnosis. CC screening (CCS) is key to preventing these deaths. Awareness of past CCS, its determinants, and uptake of CCS after receiving information is crucial to informing prevention programming.MethodsA two-phase community based cross-sectional survey was conducted among 600 randomly selected women aged 25-65 years, from two Ugandan districts (Mukono and Wakiso). Participants completed a baseline questionnaire that assessed their knowledge, attitudes, and past practices related to CCS. Information on cervical cancer and screening was provided during and after the survey to encourage uptake, which was assessed three months later. Logistic regression identified factors associated with past CCS and follow-up uptake after information giving.ResultsFew women [5.3%, (32/600)] were aware that Human Papillomavirus (HPV) infection causes CC. Past CCS was low [22.3%, (134/600)], associated with the age group 36-65 years (AOR= 1.9, 95% CI 1.2 - 3.2), owning a mobile telephone (AOR = 2.3, 95% CI 1.4 - 3.9), residing in a household headed by someone with tertiary or higher education (AOR=2.6, 95% CI 1.3 - 5.0), self-reported HIV infection (AOR=10.5, 95% CI 5.2 - 21.3), awareness of the location of CCS services (AOR=3.2, 95% CI 1.3 - 7.8), and awareness that accessing the CCS location was not expensive (AOR=2.3, 95% CI 1.3 - 4.0).The uptake of CCS following information provision was 40.3%, (236/585), associated with employment (AOR=2.7, 95% CI 1.2 - 5.8), moderate-high income (AOR=1.6, 95% CI 1.0 - 2.6), and prior receipt of CCS services (AOR 6.7, 95% CI 4.0 -11.2).ConclusionCCS remains low but is higher among women with better socioeconomic status, awareness of services, and HIV infection. Targeted strategies addressing awareness and motivating women to get screened can boost screening uptake.

IntroductionThe introduction of proteasome inhibitors and immunomodulatory agents has significantly improved the prognosis of multiple myeloma (MM). However, the occurrence of second primary malignancies (SPMs) in MM survivors has raised widespread concern.MethodsThis population-based retrospective study using the SEER database analyzed data from 26,869 MM patients (1990-2021) to evaluate changes in SPMs across two therapeutic eras. Patients were stratified into two therapeutic eras based on the year of MM diagnosis: Era-1 (1990-2005; n=12,858) and Era-2 (2006-2021; n=14,011).ResultsAmong 1,346 MM patients who developed SPMs, 670 were in Era-1 and 676 in Era-2. The 15-year cumulative incidence of SPMs was significantly higher in Era-2 (7.7% vs. 4.8%, P < 0.001), an increase driven mainly by solid tumors (6.90% vs. 4.10%, P < 0.001) with no significant change in second hematological malignancies (0.84% vs. 0.67%, P = 0.13). Standardized incidence ratio (SIR) analysis revealed elevated hematological malignancy risk in Era-2 (SIR = 1.71, 95% CI: 1.49-1.96). Median time to SPM was shorter in Era-2 (43.5 vs. 59 months, P < 0.001). Notably, 80% of SPMs in Era-2 occurred within 90 months of MM diagnosis. Overall survival (OS) of SPM patients showed no significant improvement in Era-2 compared to Era-1. Within each diagnostic era, patients who developed SPMs exhibited longer overall survival than those with MM alone; however, this reflects survivor bias, as SPMs can only develop in patients who survive long enough after the initial MM diagnosis. No significant OS differences were observed among SPM patients by race or gender.ConclusionsThe risk of SPMs in MM survivors has significantly increased, and the latency between MM diagnosis and the onset of SPMs was shorter in the Era-2, highlighting the need for enhanced cancer surveillance in MM survivors.

IntroductionCervical cancer (CC) is the third most prevalent malignancy among women worldwide. Candidate gene studies have identified multiple single nucleotide polymorphisms (SNPs) that are associated with an increased risk of CC. The objective of this study was to examine the relationship between 8 specific single-nucleotide polymorphisms (SNPs) and the risk of cervical cancer in the Georgian population.MethodsThe present study employed a prospective case-control design, with 40 patients diagnosed with CC and 45 healthy women. A total of 8 single-nucleotide polymorphisms (SNPs) were genotyped using the TaqMan genotyping assay: rs7579014, rs11263763, rs7726159, rs6897196, rs2853672, rs635634, rs231775, and rs2304204.ResultsOur analysis demonstrated that rs7579014 (BCL11A, G/A), rs7726159 (TERT, C/A), and rs6356634 (ABO, T/A) were associated with an increased risk of cervical cancer in Georgian patients. However, following the implementation of the Benjamini-Hochberg correction, only rs6356634 (ABO T/A) and rs7579014 (BCL11A G/A) remained statistically significant. A lack of statistically significant correlation was identified between the genetic variants rs11263763, rs6897196, rs2853672, rs2304204, and rs231775 and susceptibility to cervical cancer.ConclusionsThis study represents the first attempt to investigate SNP associations in women with cervical cancer in Georgia. The findings indicate that SNP-based analysis may hold promise for the early identification of susceptibility to cervical cancer, and potentially to other cancers. Nevertheless, further research involving larger sample sizes is required to validate and strengthen these preliminary observations.

IntroductionQuantifying disease burden plays a critical role in informing prevention strategies and optimizing health resource allocation. While existing studies have separately described the global epidemiological landscapes of chronic obstructive pulmonary disease (COPD) and tracheal, bronchus, and lung cancer (LC), there is a notable absence of comprehensive analysis on the combined burden of LC-COPD. Addressing this gap is essential for improving disease management and policy development.MethodsData on age-standardized incidence, death, prevalence, and disability-adjusted life year (DALY) rates (ASIR, ASDR, ASPR, and ASDALYR per 100 000) from 1990 to 2021, in global, regional, and national/territorial hierarchy, were retrieved from the 2021 Global Burden of Disease Study (GBD 2021). COPD to LC ratios of ASRs (C/L-ASRs) were calculated to describe the relative burden of LC-COPD. With Joinpoint regression, the average annual percentage changes were generated to study epidemiological trends. ASDALYR attributable to four shared risks, were systematically studied.ResultsIn 2021, global ASRs for both COPD and LC declined, yet their combined disease burden remained substantial. Notably, five regions exhibited synchronous increases. Low SDI regions showed severe imbalance-described by a C/L-ASIR of 3.53 in 2021. Age stratification further revealed COPD-dominated mortality in aged ≥ 75 years, particularly among females. Despite a 60.1% global decline since 1990, smoking was still the leading contributor. Household air pollution from solid fuels posed a greater burden than smoking in South Asia and Sub-Saharan Africa. Ambient particulate matter pollution increased LC-related ASDALYRs in almost all regions.ConclusionAlthough the overall burden of LC-COPD is declining, the comorbid population remains large and continues to face healthcare access barriers. This study calls for shifting focus to the shared comorbidity burden, prioritizing the prevention of common risk factors, early identification of comorbidities, and implementing integrated care to optimize resource utilization under constrained conditions.