Adherence to cardiovascular disease risk factor medications among patients with cancer: a systematic review.

PURPOSE: The most common cause of mortality for many cancer survivors is cardiovascular disease (CVD). This requires a shift in thinking where control of CVD risk factor-related comorbidity is paramount. Our objective was to provide an understanding of adherence to medications for the management of CVD risk factor-related comorbidities among cancer survivors. METHODS: We systematically searched for articles indexed in MEDLINE (via PubMed), Embase, Cochrane (Wiley), PsycINFO, and Scopus (via Elsevier) for articles published from inception to October 31, 2019, and updated the search on June 7, 2021. English language, original research that assessed medication adherence to common CVD risk factor-related comorbidities among cancer survivors was included. We assessed risk of bias using the Mixed Methods Appraisal Tool. RESULTS: Of the 21 studies included, 57% focused on multiple cancer types. Seventy-one percent used pharmacy-based adherence measures. Two were prospective. Adherence was variable across cancer types and CVD risk factor-related comorbidities. Among the studies that examined changes in comorbid medication adherence, most noted a decline in adherence following cancer diagnosis and throughout cancer treatment. There was a focus on breast cancer populations. CONCLUSIONS: CVD risk factor-related medication adherence is low among cancer survivors and declines over time. Given the risk for CVD-mortality among cancer survivors, testing of interventions aimed at improving adherence to non-cancer medications is critically needed. IMPLICATIONS FOR CANCER SURVIVORS: For many cancer survivors, regularly taking medications to manage CVD risk is important for longevity. Engaging with primary care throughout the cancer care trajectory may be important to support cardiovascular health.

Opioid Prescribing and Use Among Cancer Survivors: A Mapping Review of Observational and Intervention Studies.

CONTEXT: Recent years show a sharp increase in research on opioid use among cancer survivors, but evidence syntheses are lacking, leaving knowledge gaps. Corresponding research needs are unclear. OBJECTIVES: To provide an evidence synthesis. METHODS: We searched PubMed and Embase, identifying articles related to cancer, and opioid prescribing/use published through September 2020. We screened resulting titles/abstracts. Relevant studies underwent full-text review. Inclusion criteria were quantitative examination of and primary focus on opioid prescribing or use, and explicit inclusion of cancer survivors. Exclusion criteria included end-of-life opioid use and opioid use as a secondary or downstream outcome (for intervention studies). We extracted information on the opioid-related outcome(s) examined (including definitions and terminology used), study design, and methods. RESULTS: Research returned 16,591 articles; 296 were included. Only 22 of 296 studies evaluated an intervention. There were 105 studies evaluating outcomes indicative of potentially high-risk, nonrecommended, or avoidable opioid use, e.g., continuous use-described as chronic use, prolonged use, and persistent use (n = 17); use after completion of curative-intent treatment-described as chronic opioid use, long-term opioid use, persistent opioid use, prolonged opioid use, continued opioid use, late opioid use, post-treatment opioid use (n = 27); use of opioids concurrent with other potentially high-risk medications (n = 13), and opioid misuse (n = 14). CONCLUSIONS: We found lack of consistency in the measurement of and terms used to describe similar opioid use outcomes, and a lack of interventional research targeting well-documented patterns of potentially nonrecommended, potentially avoidable, or potentially high-risk opioid prescribing or use.

Addressing Barriers to Fertility Preservation for Cancer Patients: The Role of Oncofertility Patient Navigation.

BACKGROUND: Infertility is a common late effect for cancer survivors. Whereas assisted reproductive technology has made it possible for survivors to take steps to preserve fertility before starting treatment, only a minority of patients proceed with preservation. Patient-, provider-, health system-, and societal-level barriers to fertility preservation (FP) exist. Oncofertility patient navigation is a valuable resource for addressing FP barriers. OBJECTIVES: To highlight the critical role of oncofertility patient navigation in addressing barriers to FP within an academic oncofertility program. METHODS: The role of the oncofertility patient navigator in reducing FP barriers, promoting informed decision-making, and ensuring program sustainability is described. Program metrics illustrating the impact of oncofertility patient navigation on referrals for FP counseling and access to FP in the last year also are provided. DISCUSSION: The oncofertility program at our academic adult and pediatric medical centers aims to facilitate rapid referral to fertility counseling and preservation services for postpubertal cancer patients. The patient navigator is integral to the success of the program. The navigator ensures that patients are: (1) well-informed about the potential impact of cancer on fertility and FP options, (2) aware of available resources (eg, financial) for pursuing FP, (3) able to access FP services if desired, and (4) well supported in making an informed FP decision. The inclusion of the patient navigator has led to an almost 2-fold increase in referrals for FP counseling in the past year over the historic annual average. CONCLUSIONS: Our institution's oncofertility program, with patient navigation at the core, provides a potential model for increasing patient access to oncofertility care and promoting program sustainability. Oncofertility patient navigation is a valuable resource for providing patients and families with education and support regarding FP decision-making, as well as addressing the multilevel barriers to FP.

Implementation and Impact of a Risk-Stratified Prostate Cancer Screening Algorithm as a Clinical Decision Support Tool in a Primary Care Network.

BACKGROUND: Implementation methods of risk-stratified cancer screening guidance throughout a health care system remains understudied. OBJECTIVE: Conduct a preliminary analysis of the implementation of a risk-stratified prostate cancer screening algorithm in a single health care system. DESIGN: Comparison of men seen pre-implementation (2/1/2016-2/1/2017) vs. post-implementation (2/2/2017-2/21/2018). PARTICIPANTS: Men, aged 40-75 years, without a history of prostate cancer, who were seen by a primary care provider. INTERVENTIONS: The algorithm was integrated into two components in the electronic health record (EHR): in Health Maintenance as a personalized screening reminder and in tailored messages to providers that accompanied prostate-specific antigen (PSA) results. MAIN MEASURES: Primary outcomes: percent of men who met screening algorithm criteria; percent of men with a PSA result. Logistic repeated measures mixed models were used to test for differences in the proportion of individuals that met screening criteria in the pre- and post-implementation periods with age, race, family history, and PSA level included as covariates. KEY RESULTS: During the pre- and post-implementation periods, 49,053 and 49,980 men, respectively, were seen across 26 clinics (20.6% African American). The proportion of men who met screening algorithm criteria increased from 49.3% (pre-implementation) to 68.0% (post-implementation) (p < 0.001); this increase was observed across all races, age groups, and primary care clinics. Importantly, the percent of men who had a PSA did not change: 55.3% pre-implementation, 55.0% post-implementation. The adjusted odds of meeting algorithm-based screening was 6.5-times higher in the post-implementation period than in the pre-implementation period (95% confidence interval, 5.97 to 7.05). CONCLUSIONS: In this preliminary analysis, following implementation of an EHR-based algorithm, we observed a rapid change in practice with an increase in screening in higher-risk groups balanced with a decrease in screening in low-risk groups. Future efforts will evaluate costs and downstream outcomes of this strategy.

Prevalence of traditional, complementary, and alternative medicine use by cancer patients in low income and lower-middle income countries.

The use of traditional, complementary, and alternative medicine (TCAM) for cancer may influence the delivery or effectiveness of conventional cancer treatment. In this systematic review, we aimed to (1) summarise the available prevalence data on traditional medicine use by cancer patients in less developed countries (LDCs), and (2) stratify the prevalence data by world region and country income level. A literature search for cancer, TCAM, and low income (LI) and lower-middle income (LMI) countries was conducted across 5 databases. A total of 2,365 publications were reviewed for eligibility, of which 25 studies met inclusion criteria. The combined sample size was 6,878 cancer patients, with a median of 54.5% reporting the use of TCAM for cancer care. Of the studies providing data on the concomitant use of TCAM and conventional cancer treatment (n = 4,872 cancer patients), a median of 26.7% of participants reported combining the two systems of medicine. From the data available, it is apparent that TCAM use among cancer patients in less developed countries is common; however, additional studies are needed to support the safe and effective management of cancer for patients in LI and LMI countries.

Novel genetic variants in the P38MAPK pathway gene ZAK and susceptibility to lung cancer.

The P38MAPK pathway participates in regulating cell cycle, inflammation, development, cell death, cell differentiation, and tumorigenesis. Genetic variants of some genes in the P38MAPK pathway are reportedly associated with lung cancer risk. To substantiate this finding, we used six genome-wide association studies (GWASs) to comprehensively investigate the associations of 14 904 single nucleotide polymorphisms (SNPs) in 108 genes of this pathway with lung cancer risk. We identified six significant lung cancer risk-associated SNPs in two genes (CSNK2B and ZAK) after correction for multiple comparisons by a false discovery rate (FDR) <0.20. After removal of three CSNK2B SNPs that are located in the same locus previously reported by GWAS, we performed the LD analysis and found that rs3769201 and rs7604288 were in high LD. We then chose two independent representative SNPs of rs3769201 and rs722864 in ZAK for further analysis. We also expanded the analysis by including these two SNPs from additional GWAS datasets of Harvard University (984 cases and 970 controls) and deCODE (1319 cases and 26 380 controls). The overall effects of these two SNPs were assessed using all eight GWAS datasets (OR = 0.92, 95%CI = 0.89-0.95, and P = 1.03 × 10-5 for rs3769201; OR = 0.91, 95%CI = 0.88-0.95, and P = 2.03 × 10-6 for rs722864). Finally, we performed an expression quantitative trait loci (eQTL) analysis and found that these two SNPs were significantly associated with ZAK mRNA expression levels in lymphoblastoid cell lines. In conclusion, the ZAK rs3769201 and rs722864 may be functional susceptibility loci for lung cancer risk.

Genetic variants of PTPN2 are associated with lung cancer risk: a re-analysis of eight GWASs in the TRICL-ILCCO consortium.

The T-cell protein tyrosine phosphatase (TCPTP) pathway consists of signaling events mediated by TCPTP. Mutations and genetic variants of some genes in the TCPTP pathway are associated with lung cancer risk and survival. In the present study, we first investigated associations of 5,162 single nucleotide polymorphisms (SNPs) in 43 genes of this TCPTP pathway with lung cancer risk by using summary data of six published genome-wide association studies (GWAS) of 12,160 cases and 16,838 controls. We identified 11 independent SNPs in eight genes after correction for multiple comparisons by a false discovery rate <0.20. Then, we performed in silico functional analyses for these 11 SNPs by eQTL analysis, two of which, PTPN2 SNPs rs2847297 and rs2847282, were chosen as tagSNPs. We further included two additional GWAS datasets of Harvard University (984 cases and 970 controls) and deCODE (1,319 cases and 26,380 controls), and the overall effects of these two SNPs among all eight GWAS studies remained significant (OR = 0.95, 95% CI = 0.92-0.98, and P = 0.004 for rs2847297; OR = 0.95, 95% CI = 0.92-0.99, and P = 0.009 for rs2847282). In conclusion, the PTPN2 rs2847297 and rs2847282 may be potential susceptible loci for lung cancer risk.