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Annual lung cancer screening (LCS) can decrease lung cancer-related mortality by finding cancer at earlier, more treatable stages, yet uptake remains abysmally low in the United States, especially among adults who seldom interact with the health system. Many eligible individuals are unaware that LCS exists, underscoring the critical need for scalable, population-level communication strategies that increase awareness and engagement. The aim of this study was to evaluate reach, as defined by the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework, as the extent to which the target population comes in contact with a social media-based strategy, Facebook-targeted advertisement (FBTA), designed to connect LCS-eligible individuals in the United States with a digital health communication message. The advertisement served as a digital outreach strategy for promoting engagement with LungTalk, an evidence-based intervention aimed at increasing awareness and informed decision-making about LCS. As part of the INSPIRE-Lung Study (INnovating Social Media for Prevention: LUNG Cancer Screening Awareness, Knowledge, and Uptake), 5 FBTA campaigns were launched over a 79-day period throughout the United States. Advertisements targeted adults aged 50-80 years with interests related to smoking or smoking cessation and linked to a study website where participants could complete an eligibility screener and learn more about the trial. Facebook analytics were used to assess reach, defined by the number, proportion, and demographic characteristics of individuals exposed to and interacting with FBTA content. Key metrics included total reach, impressions, link clicks, and cost-efficiency. The FBTA campaigns reached 1,048,191 unique users and generated 3,109,482 impressions (total advertisement displays, including repeat exposures to the same user). A total of 24,816 individuals clicked on the advertisements (2.37% click-through rate), and 7117 completed the eligibility screener. Of those eligible, 1272 (17.9%) met lung screening criteria, and of these, 483 (38% participation rate) enrolled in the trial. The cost per click was US $0.40, and the cost per enrolled participant was US $19.46. Individuals reached via FBTA were demographically diverse and included many who may be disconnected from traditional health care systems. FBTA is a scalable, cost-effective strategy to achieve population-level reach of LCS-eligible adults. By conceptualizing reach as exposure to an upstream digital message rather than enrollment alone, this study illustrates how social media can broaden population access to evidence-based cancer prevention tools such as LungTalk. Future research should explore embedding intervention content directly into social media platforms and tracking downstream clinical outcomes.

During the diagnosis and treatment of non-small cell lung cancer (NSCLC), detecting the risk of its recurrence in an early phase is still challenging. Recent studies have investigated the radiomics-based machine learning (ML) models for detecting the risk of recurrence in NSCLC. However, there is still insufficient systematic evidence to prove its efficiency. This study is designed to systematically evaluate the effectiveness of radiomics-based ML in predicting the risk of recurrence in NSCLC, aiming to provide evidence-based support for the subsequent development of scoring tools to forecast recurrence risk. For acquiring research on radiomics-based models for forecasting the risk of recurrence in NSCLC, Cochrane Library, Web of Science, PubMed, and Embase were systematically retrieved, up to October 24, 2025. Studies on analyzing the recurrence of NSCLC using radiomics-based ML were included, while those in which only texture analysis was conducted or radiomics-based ML was not constructed were excluded. The Radiomics Quality Score (RQS) was used to appraise the eligible studies. Subgroup analyses were conducted according to the variables of the model, the background of treatment, the stage of lung cancer, and the pathological type. Ultimately, 30 eligible studies in total were included, covering 7964 patients with NSCLC. According to the meta-analysis, the c-index of radiomics-based ML models for forecasting the risk of recurrence in NSCLC was 0.850 (95% CI 0.834-0.866, 95% prediction interval [PI] 0.623-1.004) in the training set. Specifically, the pooled c-index was 0.876 (95% CI 0.853-0.900) among the patients receiving the stereotactic body radiation therapy and 0.825 (95% CI 0.804-0.848) among those who received surgeries combined with other adjuvant treatment regimens. The c-index of the radiomics-based ML models combined with clinical features for forecasting the risk of recurrence in NSCLC was 0.833 (95% CI 0.822-0.854, 95% PI 0.717-0.945) in the training set. In contrast, the c-index of radiomics-based ML models for forecasting the risk of recurrence in NSCLC was 0.878 (95% CI 0.854-0.902, 95% PI 0.681-1.000) in the validation set. The c-index of radiomics-based ML models combined with clinical features for forecasting the risk of recurrence in NSCLC was 0.854 (95% CI 0.830-0.878, 95% PI 0.655-0.992) in the validation set. The average RQS across the included studies was 27.4%, revealing methodological limitations and an absence of standardization. This study is the first to confirm that radiomics-based ML models effectively predict the risk of recurrence in NSCLC. This study provides evidence-based support for the subsequent development or updating of radiomics-based ML models. However, the current methodological application of radiomics remains concerning. Therefore, in the future, research should standardize the workflow for implementing radiomics-based ML and incorporate multicenter imaging data to enhance its generalizability.

Cancer remains one of the foremost global causes of mortality, with nearly 10 million deaths recorded by 2020. As incidence rates rise, there is a growing interest in leveraging machine learning (ML) to enhance prediction, diagnosis, and treatment strategies. Despite these advancements, insufficient attention has been directed toward the integration of sociodemographic variables, which are crucial determinants of health equity, into ML models in oncology. This review aims to investigate how ML techniques have been used to identify patterns of predictive association between sociodemographic factors and cancer-related outcomes. Specifically, it seeks to map current research endeavors by detailing the types of algorithms used, the sociodemographic variables examined, and the validation methodologies used. We conducted a systematic literature review in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Searches were executed across 6 databases, focusing on the primary studies using ML to investigate the association between sociodemographic characteristics and cancer-related outcomes. The search strategy was informed by the PICO (population, intervention, comparison, and outcome) framework, and a set of predefined inclusion criteria was used to screen the studies. The methodological quality of each included paper was assessed. Out of the 328 records examined, 19 satisfied the inclusion criteria. The majority of studies used supervised ML techniques, with random forest and extreme gradient boosting being the most commonly used. Frequently analyzed variables include age, male or female or intersex, education level, income, and geographic location. Cross-validation is the predominant method for evaluating model performance. Nevertheless, the integration of clinical and sociodemographic data is limited, and efforts toward external validation are infrequent. ML holds significant potential for discerning patterns associated with the social determinants of cancer. Nevertheless, research in this domain remains fragmented and inconsistent. Future investigations should prioritize the integration of contextual factors, enhance model transparency, and bolster external validation. These measures are crucial for the development of more equitable, generalizable, and actionable ML applications in cancer care.

Disseminating disease knowledge through concise videos on various platforms is an innovative and efficient approach. However, it remains uncertain whether pancreatic neuroendocrine tumor (pNET)-related videos available on current short video platforms can effectively convey accurate and impactful information to the general public. Our study aims to extensively analyze the quality of pNET-related videos on TikTok and Bilibili, intending to enhance the development of pNET-related social media content to provide the general public with more comprehensive and suitable avenues for accessing pNET-related information. A total of 168 qualifying videos pertaining to pNETs were evaluated from the video-sharing platforms Bilibili and TikTok. Initially, the fundamental information conveyed in the videos was documented. Subsequently, we discerned the source and content type of each video. Following that, the Global Quality Scale (GQS) and modified DISCERN (mDISCERN) scale were employed to appraise the educational value and quality of each video. A comparative evaluation was conducted on the videos obtained from these two platforms. The number of pNET-related videos saw a significant increase since 2020, with 9 videos in 2020, 19 videos in 2021, 29 videos in 2022, and 106 videos in 2023. There were no significant improvements in the mean GQS or mDISCERN scores from 2020 to 2023, which were 3.22 and 3.00 in 2020, 3.33 and 2.94 in 2021, 2.83 and 2.79 in 2022, and 2.78 and 2.94 in 2023, respectively. The average quality scores of the videos on Bilibili and Tiktok were comparable, with GQS and mDISCERN scores of 2.98 on Bilibili versus 2.77 on TikTok and 2.82 on Bilibili versus 3.05 on TikTok, respectively. The source and format of the videos remained independent factors affecting the two quality scores. Videos that were uploaded by professionals (hazard ratio=7.02, P=.002) and recorded in specialized popular science formats (hazard ratio=12.45, P<.001) tended to exhibit superior quality. This study demonstrates that the number of short videos on pNETs has increased in recent years, but video quality has not improved significantly. This comprehensive analysis shows that the source and format of videos are independent factors affecting video quality, which provides potential measures for improving the quality of short videos.

Published evidence on patient experiences, perceptions, and challenges related to early breast cancer (eBC) in Italy is limited. Understanding these aspects is critical for improving diagnosis, treatment outcomes, and quality of life (QoL). This study used social media listening (SML) to explore the patient journey, treatment perceptions, QoL, and unmet needs of patients with eBC, caregivers, and health care professionals (HCPs) in Italy. This retrospective noninterventional SML study analyzed publicly available posts from December 2021 to November 2023 using breast cancer-related keywords in English and Italian through Sprinklr, a web-based aggregator tool. Posts sourced from social media platforms, such as X (formerly known as Twitter), blogs, forums, Facebook, Instagram, and YouTube, were filtered by geographic location to include only users in Italy. Posts were filtered using natural language processing (NLP) for relevance and duplicates, followed by manual review and stakeholder identification (patients, caregivers, and HCPs). Key themes of discussion were identified through thematic analysis of posts across the stages of the patient journey (symptoms, diagnosis, treatment, etc). Ethical guidelines were followed by using anonymized, publicly available data. Descriptive statistics were used to analyze the data, and posts with missing data were excluded. Consequently, denominators varied across analyses and were adjusted based on data availability for specific variables. Of the 20,008 posts initially extracted, 1580 posts were retained following NLP filtering, and 530 posts were included after manual screening. The majority (493/518, 95%) of the posts were sharing information about diagnosis and treatment journeys, emotional challenges, QoL concerns, and symptoms (eg, lumps, breast pain), while 27% (141/518) of the posts sought information on diagnostic dilemmas, treatment options, and second opinions. Patients contributed 60% (318/530) of the posts, and caregivers contributed 21% (111/530) of the posts, with over half (57/107, 53%) discussing their mothers' diagnosis and treatment struggles. HCPs contributed 16% (85/530) of the posts, primarily sharing clinical trial updates, drug approvals, and disease awareness efforts. A total of 88 posts included discussions on QoL, and eBC significantly impacted patients' emotional, physical, functional, and social well-being. Discussions revealed key unmet needs, including limited awareness of adjuvant therapy options, lack of peer support groups, suboptimal patient-HCP communication, and insufficient access to specialty care facilities. This study highlights gaps in eBC management related to patient education, HCP communication, and access to specialty care and describes an associated worsening of QoL for patients as reflected in social media posts. Within the limitations of an observational SML design, increasing patient and caregiver awareness of available adjuvant therapies to improve adherence and reduce recurrence risk, alongside expanding access to regional breast cancer centers, may help optimize patient experiences and outcomes. Further research using complementary data sources is needed to confirm and extend these findings.

Growing interest surrounds how internet search behaviors might provide digital signals of disease prior to diagnosis, for example, when people search symptoms online. Internet browsing data offer novel opportunities for understanding response to symptoms, public health surveillance, and early intervention in conditions such as cancer. However, the acceptability of using such sensitive data in medical research remains unclear, particularly among individuals at higher risk of health and digital exclusion, such as older adults and those from minority ethnic groups or with a lower socioeconomic status. This study aims to explore the feasibility and acceptability of using internet browsing history data for health research. Participants were purposively sampled to ensure representation from groups at risk of digital and health inequalities via community organizations and charities. We conducted semistructured and think-aloud interviews allowing participants to reflect on hypothetical research involving sharing their internet browsing data. The adapted theoretical framework of acceptability guided the interview structure and coding. The interviews were transcribed, coded in NVivo, and thematically analyzed. Patient and public involvement informed the study approach, participant-facing documents, and the interpretation of the findings. Twenty participants (10 with a history of cancer and 10 without) were included in the study representing a range of age, gender, and ethnic and socioeconomic groups. Key themes focused on factors necessary for acceptability, including trust, transparency, and control and on perceived feasibility and individual willingness. Trust and transparency were fundamental to participants' willingness to share data. Trust in researchers would have to be earned through clear communication, ethical data handling, and familiarity with a named research team. Privacy concerns were prominent, with participants wanting control over what was shared, particularly regarding nonhealth-related information (such as details related to banking) or activity related to others (such as their children). Potential use or misuse of data beyond the original research purpose caused more concern than the nature of the shared data itself. Digital literacy varied; many expressed concerns over the technical aspects of sharing data. Participants also doubted the value of their individual internet browsing history, for example, as they chose not to search for health information due to the prevalence of misinformation. However, they described wider benefits arising from internet browsing history research, such as potential advancements in early detection and opportunities to promote credible online sources. Participant recommendations balanced privacy concerns against the potential of internet history data for early diagnosis and health research. The study highlights ethical and inclusive approaches to health research using internet browsing history. Future researchers should consider defining the scope of health-specific data filters, providing user-friendly information and guidance for study participants, and ensuring that participants are able to contact research team members to build trust and facilitate data sharing.

Breast cancer is a major health concern in various countries. Routine mammography screening has been shown to reduce breast cancer mortality, and Japan has set national targets to improve screening participation and increase public attention. However, collecting nationwide data on public attention and activity is not easy. Google Trends can reveal changes in societal interest, yet there are no reports on the relationship between internet search volume and nationwide participation rates in Japan. This study aims to reveal and discuss the relationship between public awareness and actual behavior in breast cancer screening by examining trends in internet search volume for the keyword \"breast cancer screening\" and participation rates over a decade-long period. This time-series study evaluated the association between internet search volume and breast cancer screening participation behavior among women aged 60-69 years in Japan from 2009 to 2019. Relative search volume (RSV) data for the search term \"breast cancer screening (nyuugan-kenshin)\" were extracted from Google Trends as internet search volume. Breast cancer screening and further assessment participation rates were based on government municipal screening data. Joinpoint regression analyses were conducted with weighted BIC to evaluate the time trends. An ethics review was not required because all data were open. The RSV for \"breast cancer screening (nyuugan-kenshin)\" peaked in June 2017 (100) and showed clear spikes in June 2016 (94), September (69), and October (77) 2015. No RSVs above 60 were observed except around these three specific periods, and the average RSV for the entire period was 30.7 (SD 16.2). Two statistically significant joinpoints were detected, rising in December 2013 and falling in June 2017. Screening participation rates showed a temporary increase in 2015 in a slowly decreasing trend, and no joinpoints were detected. Further assessment participation rates showed a temporary spike in 2015 in the middle of an increasing trend, with a statistically significant point of slowing increase detected in 2015. Post hoc manual searches revealed that Japanese celebrities' breast cancer diagnoses were announced on the relevant dates, and many Japanese media reports were found. This study found a notable association between internet search activity and celebrity cancer media reports and a temporal association with screening participation in breast cancer screening in Japan. Celebrity cancer media reports triggered internet searches for cancer screening, but this did not lead to long-term changes in screening participation behavior. This finding suggests what information needs to be provided to citizens to encourage participation in screening.

Mental health is becoming increasingly recognized as an important part of overall health, especially for patients with cancer. However, the relationship between nonmelanoma skin cancer and mental health has not been widely studied. The aim of this study was to examine the association between nonmelanoma skin cancer diagnosis and 2 key mental health outcomes (ie, clinical depression and the number of poor mental health days). This study used the 2023 Behavioral Risk Factor Surveillance System, a nationally representative survey of adults in the United States, which included 312,317 participants. Nonmelanoma skin cancer diagnosis, depression, and self-reported mental health days were analyzed. Logistic regression was used to evaluate the association between nonmelanoma skin cancer and depression, whereas Poisson regression was used to model the number of poor mental health days, adjusting for age, sex, race and ethnicity, education, BMI, income, and major comorbid conditions (other cancers, heart disease, lung disease, and kidney disease). Individuals with nonmelanoma skin cancer (5086/26,552, 19.15%) reported a lower overall rate of depression compared to those without nonmelanoma skin cancer (61,438/285,765, 21.50%; P<.001) but reported more poor mental health days on average (4.54, SD 8.37 d vs 3.20, SD 7.37 d; P<.001). After adjustment, nonmelanoma skin cancer diagnosis was not significantly associated with depression (adjusted odds ratio 1.01, 95% CI 0.98-1.05) and was associated with a slightly lower number of poor mental health days (adjusted rate ratio 0.94, 95% CI 0.91-0.97). Adults with nonmelanoma skin cancer experienced a meaningful mental health burden, and unadjusted analyses suggested greater day-to-day distress than among adults without nonmelanoma skin cancer. However, these differences were reduced and no longer significant for depression after adjusting for sociodemographic factors and comorbid chronic illnesses. These findings support the need for mental health screenings and support services in dermatologic and oncologic care.

Effective prevention and treatment are urgently needed, since gastric cancer (GC) poses a grave threat to the health and well-being of patients. The 5 East Asian countries (China, Japan, North Korea, South Korea, and Mongolia) represent one of the most significant regions globally in terms of GC burden. The goal of this study is to examine the patterns and trends of GC across 5 East Asian countries between 1990 and 2021. We retrieved data from the Global Burden of Disease Study (GBD) 2021 regarding the prevalence, incidence, mortality, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life years (DALYs) associated with GC in 5 East Asian countries from 1990 to 2021. We further assessed the burden of GC according to age and sex. We used decomposition analysis to examine the changes in the number of new cases, patients, and deaths related to GC. We also used Joinpoint (Joinpoint Regression Program, Version 5.1.0) and age-period-cohort analysis methods to interpret the epidemiological characteristics of GC. Autoregressive integrated moving average model (ARIMA) and Bayesian age-period-cohort (BAPC) prediction models were used to forecast the GC burden by 2036. Among the 5 East Asian countries, China recorded the highest incidence, prevalence, death, YLLs, YLDs, and DALYs in both 1990 and 2021. From 1990 to 2021, the age-standardized rates for prevalence, mortality, incidence, YLDs, YLLs, and DALYs across the 5 East Asian countries showed an overall decline, though they remained higher than the global average. In all 5 East Asian countries, individuals aged 65 years and older consistently exhibited the highest rates for prevalence, incidence, mortality, YLDs, YLLs, and DALYs. The prevalence rate in South Korea, the incidence rate in North Korea and Mongolia, and the mortality rate in China are influenced by aging, surpassing the global aging average. The disease burden of GC in the 5 East Asian countries has consistently ranked high over the past 3 decades, particularly among the older individuals. The burden of GC in the 5 East Asian countries is expected to present a major public health challenge, primarily driven by the large population size and the aging demographic.

Currently, head and neck cancer (HNC) associated with pesticide exposure represents a global public health concern. However, there is no consensus regarding the specific determinants involved in this association. Moreover, there is a lack of scientific evidence to support the development of systematic reviews on this topic. This study aims to synthesize the methodology for conducting a systematic review to explore the current scientific evidence on the determinants of HNC associated with pesticides. The review will follow the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines to ensure methodological rigor. The protocol includes detailed steps for constructing a robust search strategy using relevant databases such as PubMed, Embase, Scopus, Web of Science, CINAHL, LILACS, and AGRICOLA. Keywords and Medical Subject Headings terms related to \"pesticides,\" \"exposure,\" \"head and neck neoplasms,\" and related concepts will be used to capture the most relevant studies. Eligibility criteria will be clearly defined, including study design (eg, cohort, case-control, and cross-sectional), population characteristics, exposure assessment, and cancer outcomes. Studies published in any language that involve human participants will be included. The studies will be screened in 2 phases: first by title and abstract and then by full-text review. Two independent reviewers will assess the quality of each study and extract key data, such as exposure levels, cancer subtypes, and effect sizes. Any disagreements will be resolved through discussion or by a third reviewer. This systematic review was initiated in February 2025 after protocol registration. The literature search and review process is ongoing at the time of submission of this paper. Data extraction and quality assessment have not yet been completed. Final results of the review, including a synthesis of determinants associated with pesticide exposure in patients with HNC, are expected to be completed and submitted for publication in June 2026. The necessary steps to conduct a systematic review must be concise and publicly available to ensure replicability within the scientific community.