Causes of Childhood Cancer: A Review of the Recent Literature: Part I-Childhood Factors.

PURPOSE: To review the childhood risk factors for pediatric cancer (diagnosis before age 20). METHODS: We conducted literature searches using Ovid Medline and Scopus to find primary research studies, review articles, and meta-analyses published from 2014 to 3 March 2021. RESULTS: Strong evidence indicates that an array of genetic and epigenetic phenomena, structural birth defects, and chromosomal anomalies are associated with an increased risk of various childhood cancers. Increased risk is also associated with prior cancer, likely due to previous treatment agents and therapeutic ionizing radiation. Convincing evidence supports associations between several pediatric cancers and ionizing radiation, immunosuppression, and carcinogenic virus infection both in healthy children and in association with immune suppression following organ transplantation. Breastfeeding and a childhood diet rich in fruits and vegetables appears to reduce the risk of pediatric leukemia but the evidence is less strong. Childhood vaccination against carcinogenic viruses is associated with a lower risk of several cancers; there is less strong evidence that other childhood vaccinations more broadly may also lower risk. Ultraviolet (UV) radiation is associated with increased melanoma risk, although most melanomas following childhood UV exposure occur later, in adulthood. Evidence is weak or conflicting for the role of body mass index, other childhood infections, allergies, and certain treatments, including immunomodulator medications and human growth therapy.

Adoption of Telemedicine in a Rural US Cancer Center Amid the COVID-19 Pandemic: Qualitative Study.

BACKGROUND: The COVID-19 pandemic necessitated a rapid shift to telemedicine to minimize patient and provider exposure risks. While telemedicine has been used in a variety of primary and specialty care settings for many years, it has been slow to be adopted in oncology care. Health care provider and administrator perspectives on factors affecting telemedicine use in oncology settings are not well understood, and the conditions associated with the COVID-19 pandemic offered the opportunity to study the adoption of telemedicine and the resulting provider and staff perspectives on its use. OBJECTIVE: The aim of this paper is to study the factors that influenced telemedicine uptake and sustained use in outpatient oncology clinics at a US cancer center to inform future telemedicine practices. METHODS: We used purposive sampling to recruit a mix of oncology specialty providers, practice managers, as well as nursing and administrative staff representing 5 outpatient oncology clinics affiliated with the Dartmouth Cancer Center, a large regional cancer center in the northeast of United States, to participate in semistructured interviews conducted over 6 weeks in spring 2021. The interview guide was informed by the 5 domains of the Consolidated Framework for Implementation Research, which include inner and outer setting factors, characteristics of the intervention (ie, telemedicine modality), individual-level factors (eg, provider and patient characteristics), and implementation processes. In total, 11 providers, 3 leaders, and 6 staff participated following verbal consent, and thematic saturation was reached across the full sample. We used a mixed deductive and inductive qualitative analysis approach to study the main influences on telemedicine uptake, implementation, and sustainability during the first year of the COVID-19 pandemic across the 5 settings. RESULTS: The predominant influencers of telemedicine adoption in this study were individual provider experiences and assumptions about patient preference and accessibility. Providers' early telemedicine experiences, especially if negative, influenced preferences for telephone over video and affected sustained use. Telemedicine was most favorably viewed for lower-acuity cancer care, visits less dependent on physical exam, and for patient and caregiver education. A lack of clinical champions, leadership guidance, and vision hindered the implementation of standardized practices and were cited as essential for telemedicine sustainability. Respondents expressed anxiety about sustaining telemedicine use if reimbursements for telephonic visits diminished or ceased. Opportunities to enhance future efforts include a need to provide additional guidance supporting telemedicine use cases and evidence of effectiveness in oncology care and to address provider concerns with communication quality. CONCLUSIONS: In a setting of decentralized care processes, early challenges in telemedicine implementation had an outsized impact on the nature and amount of sustained use. Proactively designed telemedicine care processes with attention to patient needs will be essential to support a sustained role for telemedicine in cancer care.

Factors Influencing Telemedicine Use at a Northern New England Cancer Center During the COVID-19 Pandemic.

PURPOSE: To characterize the use of telemedicine for oncology care over the course of the COVID-19 pandemic in Northern New England with a focus on factors affecting trends. METHODS: We performed a retrospective observational study using patient visit data from electronic health records from hematology-oncology and radiation-oncology service lines spanning the local onset of the pandemic from March 18, 2020, through March 31, 2021. This period was subdivided into four phases designated as lockdown, transition, stabilization, and second wave. Generalized linear mixed regression models were used to estimate the effects of patient characteristics on trends for rates of telemedicine use across phases and the effects of visit type on patient satisfaction and postvisit ER or hospital admissions within 2 weeks. RESULTS: A total of 19,280 patients with 102,349 visits (13.1% audio-only and 1.4% video) were studied. Patient age (increased use in age < 45 and 85 years and older) and urban residence were associated with higher use of telemedicine, especially after initial lockdown. Recent cancer therapy, ER use, and hospital admissions in the past year were all associated with lower telemedicine utilization across pandemic phases. Provider clinical department corresponded to the largest differences in telemedicine use across all phases. ER and hospital admission rates in the 2 weeks after a telehealth visit were lower than those in in-person visits (0.7% v 1.3% and 1.2% v 2.7% for ER and hospital use, respectively; P < .001). Patient satisfaction did not vary across visit types. CONCLUSION: Telemedicine use in oncology during the COVID-19 pandemic varied according to the phase and patient, medical, and health system factors, suggesting opportunities for standardization of care and need for attention to equitable telemedicine access.

Language and Sentiment Regarding Telemedicine and COVID-19 on Twitter: Longitudinal Infodemiology Study.

BACKGROUND: The COVID-19 pandemic has necessitated a rapid shift in how individuals interact with and receive fundamental services, including health care. Although telemedicine is not a novel technology, previous studies have offered mixed opinions surrounding its utilization. However, there exists a dearth of research on how these opinions have evolved over the course of the current pandemic. OBJECTIVE: This study aims to evaluate how the language and sentiment surrounding telemedicine has evolved throughout the COVID-19 pandemic. METHODS: Tweets published between January 1, 2020, and April 24, 2021, containing at least one telemedicine-related and one COVID-19-related search term ("telemedicine-COVID") were collected from the Twitter full archive search (N=351,718). A comparator sample containing only COVID-19 terms ("general-COVID") was collected and sampled based on the daily distribution of telemedicine-COVID tweets. In addition to analyses of retweets and favorites, sentiment analysis was performed on both data sets in aggregate and within a subset of tweets receiving the top 100 most and least retweets. RESULTS: Telemedicine gained prominence during the early stages of the pandemic (ie, March through May 2020) before leveling off and reaching a steady state from June 2020 onward. Telemedicine-COVID tweets had a 21% lower average number of retweets than general-COVID tweets (incidence rate ratio 0.79, 95% CI 0.63-0.99; P=.04), but there was no difference in favorites. A majority of telemedicine-COVID tweets (180,295/351,718, 51.3%) were characterized as "positive," compared to only 38.5% (135,434/351,401) of general-COVID tweets (P<.001). This trend was also true on a monthly level from March 2020 through April 2021. The most retweeted posts in both telemedicine-COVID and general-COVID data sets were authored by journalists and politicians. Whereas the majority of the most retweeted posts within the telemedicine-COVID data set were positive (55/101, 54.5%), a plurality of the most retweeted posts within the general-COVID data set were negative (44/89, 49.4%; P=.01). CONCLUSIONS: During the COVID-19 pandemic, opinions surrounding telemedicine evolved to become more positive, especially when compared to the larger pool of COVID-19-related tweets. Decision makers should capitalize on these shifting public opinions to invest in telemedicine infrastructure and ensure its accessibility and success in a postpandemic world.

Barriers, Facilitators, and Suggested Interventions for Lung Cancer Screening Among a Rural Screening-Eligible Population.

Introduction: Rural areas are disproportionally affected by lung cancer late-stage incidence and mortality. Lung cancer screening (LCS) is recommended to find lung cancer early and reduce mortality, yet uptake is low. The purpose of this study was to elucidate the barriers to, facilitators of, and suggested interventions for increasing LCS among a rural screening-eligible population using a mixed methods concurrent embedded design study. Methods: Qualitative and quantitative data were collected from rural-residing adults who met the eligibility criteria for LCS but who were not up-to-date with LCS recommendations. Study participants (n = 23) took part in 1 of 5 focus groups and completed a survey. Focus group discussions were recorded, transcribed, and coded through a mixed deductive and inductive approach. Survey data were used to enhance and clarify focus group results; these data were integrated in the design and during analysis, in accordance with the mixed methods concurrent embedded design approach. Results: Several key barriers to LCS were identified, including an overall lack of knowledge about LCS, not receiving information or recommendation from a health care provider, and lack of transportation. Key facilitators were receiving a provider recommendation and high motivation to know the screening results. Participants suggested that LCS uptake could be increased by addressing provider understanding and recommendation of LCS and conducting community outreach to promote LCS awareness and access. Conclusion: The results suggest that the rural screening-eligible population is generally receptive to LCS. Patient-level factors important to getting this population screened include knowledge, transportation, motivation to know their screening results, and receiving information or recommendation from a provider. Addressing these factors may be important to increase rural LCS uptake.

Disparities in the use of screening magnetic resonance imaging of the breast in community practice by race, ethnicity, and socioeconomic status.

BACKGROUND: Uptake of breast magnetic resonance imaging (MRI) coupled with breast cancer risk assessment offers the opportunity to tailor the benefits and harms of screening strategies for women with differing cancer risks. Despite the potential benefits, there is also concern for worsening population-based health disparities. METHODS: Among 316,172 women aged 35 to 69 years from 5 Breast Cancer Surveillance Consortium registries (2007-2012), the authors examined 617,723 negative screening mammograms and 1047 screening MRIs. They examined the relative risks (RRs) of MRI use by women with a <20% lifetime breast cancer risk and RR in the absence of MRI use by women with a ≥20% lifetime risk. RESULTS: Among women with a <20% lifetime risk of breast cancer, non-Hispanic white women were found to be 62% more likely than nonwhite women to undergo an MRI (95% confidence interval, 1.32-1.98). Of these women, those with an educational level of some college or technical school were 43% more likely and those who had at least a college degree were 132% more likely to receive an MRI compared with those with a high school education or less. Among women with a ≥20% lifetime risk, there was no statistically significant difference noted with regard to the use of screening MRI by race or ethnicity, but high-risk women with a high school education or less were less likely to undergo screening MRI than women who had graduated from college (RR, 0.40; 95% confidence interval, 0.25-0.63). CONCLUSIONS: Uptake of screening MRI of the breast into clinical practice has the potential to worsen population-based health disparities. Policies beyond health insurance coverage should ensure that the use of this screening modality reflects evidence-based guidelines.

Availability of Advanced Breast Imaging at Screening Facilities Serving Vulnerable Populations.

OBJECTIVE: Among vulnerable women, unequal access to advanced breast imaging modalities beyond screening mammography may lead to delays in cancer diagnosis and unfavourable outcomes. We aimed to compare on-site availability of advanced breast imaging services (ultrasound, magnetic resonance imaging [MRI], and image-guided biopsy) between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations. SETTING: 73 imaging facilities across five Breast Cancer Surveillance Consortium regional registries in the United States during 2011 and 2012. METHODS: We examined facility and patient characteristics across a large, national sample of imaging facilities and patients served. We characterized facilities as serving vulnerable populations based on the proportion of mammograms performed on women with lower educational attainment, lower median income, racial/ethnic minority status, and rural residence.We performed multivariable logistic regression to determine relative risks of on-site availability of advanced imaging at facilities serving vulnerable women versus facilities serving non-vulnerable women. RESULTS: Facilities serving vulnerable populations were as likely (Relative risk [RR] for MRI = 0.71, 95% Confidence Interval [CI] 0.42, 1.19; RR for MRI-guided biopsy = 1.07 [0.61, 1.90]; RR for stereotactic biopsy = 1.18 [0.75, 1.85]) or more likely (RR for ultrasound = 1.38 [95% CI 1.09, 1.74]; RR for ultrasound-guided biopsy = 1.67 [1.30, 2.14]) to offer advanced breast imaging services as those serving non-vulnerable populations. CONCLUSIONS: Advanced breast imaging services are physically available on-site for vulnerable women in the United States, but it is unknown whether factors such as insurance coverage or out-of-pocket costs might limit their use.

Advanced Breast Imaging Availability by Screening Facility Characteristics.

RATIONALE AND OBJECTIVES: To determine the relationship between screening mammography facility characteristics and on-site availability of advanced breast imaging services required for supplemental screening and the diagnostic evaluation of abnormal screening findings. MATERIALS AND METHODS: We analyzed data from all active imaging facilities across six regional registries of the National Cancer Institute-funded Breast Cancer Surveillance Consortium offering screening mammography in calendar years 2011-2012 (n = 105). We used generalized estimating equations regression models to identify associations between facility characteristics (eg, academic affiliation, practice type) and availability of on-site advanced breast imaging (eg, ultrasound [US], magnetic resonance imaging [MRI]) and image-guided biopsy services. RESULTS: Breast MRI was not available at any nonradiology or breast imaging-only facilities. A combination of breast US, breast MRI, and imaging-guided breast biopsy services was available at 76.0% of multispecialty breast centers compared to 22.2% of full diagnostic radiology practices (P = .0047) and 75.0% of facilities with academic affiliations compared to 29.0% of those without academic affiliations (P = .04). Both supplemental screening breast US and screening breast MRI were available at 28.0% of multispecialty breast centers compared to 4.7% of full diagnostic radiology practices (P < .01) and 25.0% of academic facilities compared to 8.5% of nonacademic facilities (P = .02). CONCLUSIONS: Screening facility characteristics are strongly associated with the availability of on-site advanced breast imaging and image-guided biopsy service. Therefore, the type of imaging facility a woman attends for screening may have important implications on her timely access to supplemental screening and diagnostic breast imaging services.