The American Cancer Society challenge goal to reduce US cancer mortality by 50% between 1990 and 2015: Results and reflections

Precursor Lesions, Overdiagnosis, and Oral Cancer: A Critical Review

Despite the profession placing great emphasis on oral potentially malignant disorders (OPMDs) as a gateway for early recognition and consequently better outcomes for oral cancer, the death rates for lip and oral cavity cancer have remained stagnant for three decades. Evidence shows that only a small fraction of oral cancers are in fact preceded by OPMDs, and that most OPMDs have an annual transformation rate of less than 1%. As OPMDs encompass a very heterogeneous group of oral conditions, it could be argued that only patients with oral mucosal diseases bearing a substantial risk of malignant transformation warrant close surveillance and treatment, these include proliferative leukoplakia, erythroplakia, non-homogeneous leukoplakia, as well as diseases presenting with severe dysplasia at biopsy. In this narrative review, I discuss the intricate epidemiology of the malignancies that we colloquially refer to as oral cancer, explore the limitations of focusing on OPMDs to reduce the incidence and mortality of oral cavity cancer, and argue that a may-be cancer label represents overdiagnosis for most OPMDs.

Association of Medicare eligibility with access to and affordability of care among older cancer survivors

PURPOSE

Older cancer survivors have substantial needs for ongoing care, but they may encounter difficulties accessing care due to cost concerns. We examined whether near-universal insurance coverage through Medicare-a key source of health insurance coverage in this population-is associated with improvements in care access and affordability among older cancer survivors around age 65.

METHODS

In a nationally representative sample of cancer survivors (aged 50-80) from 2006-2018 National Health Interview Survey, we employed a quasi-experimental, regression discontinuity design to estimate changes in insurance coverage, delayed/skipped care due to cost, and worries about or problems paying medical bills at age 65.

RESULTS

Medicare coverage sharply increased from 8.3% at age 64 to 98.2% at age 65, ensuring near-universal insurance coverage (99.5%). Medicare eligibility at age 65 was associated with reductions in delayed/skipped care due to cost (discontinuity, - 5.7 percentage points or pp; 95% CI, - 8.1, - 3.3; P < .001), worries about paying for medical bills (- 7.7 pp; 95% CI, - 12.0, - 3.2; P = .001), and problems paying medical bills (- 3.2 pp; 95% CI, - 6.1, - 0.2; P = .036). However, a sizable proportion reported any access or affordability problems (29.7%) between ages 66 and 80.

CONCLUSIONS

Near-universal Medicare coverage at age 65 was associated with a reduction-but not elimination-of access and affordability problems among cancer survivors.

IMPLICATIONS FOR CANCER SURVIVORS

These findings reaffirm the role of Medicare in improving access and affordability for older cancer survivor and highlight opportunities for reforms to further alleviate financial burden of care in this population.

Neurotheranostics: The Next Frontier for Health Span

With an aging U.S. population, advancements in the treatment of Alzheimer disease (AD) and other neurodegenerative diseases are key to the maximization of health span. The recent approval of 2 antiamyloid antibodies, which decrease brain amyloid load, places us on the cusp of breakthrough therapies that target the mechanism of the disease rather than just treating the symptoms. Although the trials that led to these approvals studied patients with mild early symptoms, multiple ongoing trials have enrolled cognitively normal patients screened for AD biomarkers including risk factors for amyloid positivity, family history, and genetic markers. Thus, amyloid PET can help identify an at-risk population that can be enrolled for antiamyloid therapy to prevent AD symptoms from ever developing. In this review, we examine the paradigm of neurotheranostics and how PET biomarkers of amyloid, tau, inflammation, and neurodegeneration could characterize the pathologic stage of AD and therefore allow for personalized therapy.

The need for evolutionary theory in cancer research

Sir Richard Peto is well known for proposing puzzling paradoxes in cancer biology-some more well-known than others. In a 1984 piece, Peto proposed that after decades of molecular biology in cancer research, we are still ignorant of the biology underpinning cancer. Cancer is a product of somatic mutations. How do these mutations arise and what are the mechanisms? As an epidemiologist, Peto asked if we really need to understand mechanisms in order to prevent cancer? Four decades after Peto's proposed ignorance in cancer research, we can simply ask, are we still ignorant? Did the great pursuit to uncover mechanisms of cancer eclipse our understanding of causes and preventions? Or can we get closer to treating and preventing cancer by understanding the underlying mechanisms that make us most vulnerable to this disease?

The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring

The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

BIRADS 4 - Is it possible to downgrade lesions that do not enhance on recombinant contrast-enhanced mammography images?

PURPOSE

Analysis of the morphology of lesions classified into the BI-RADS 4 category and assessment of the possibility of downgrade the BI-RADS category in those that did not show enhancement on recombinant contrast-enhanced mammography (CEM) images.

METHOD

The retrospective, single-center study included 528 patients who underwent a core needle biopsy performed from January 2017 to November 2022 due to a breast lesion classified as BI-RADS 4 on CEM. Patients' electronic records and imaging examinations were reviewed. Individual lesions were classified into the morphological categories of mass, non-mass, and microcalcifications. Sensitivity, specificity, positive as well as negative predictive values were calculated for the whole group and individual morphological categories. The influence of the lesions' diameter on the results was analyzed.

RESULTS

CEM NPV for the whole group was 93.9% (±95% CI: 90.0-96.4), for mass lesions 100% (±95% CI: 94.5-100), for non-mass lesions 97.8% (±95% CI: 87.0-99.9) and 87.9% (±95% CI: 80.3-93.0) for microcalcifications. Given that 230 out of 383 benign lesions were not contrast-enhancing, 60.1% of unnecessary CNBs would have been correctly avoided. CEM sensitivity for lesions < 20 mm was lower than for lesions ≥ 20 mm and was respectively 86.6% (±95% CI: 76.8-92.8) vs 94.6% (±95% CI: 86.0-98.2), respectively.

CONCLUSION

CEM is characterized by high sensitivity in the detection of malignant lesions in the case of lesions with mass and non-mass morphology. The high NPV for recombinant images suggests that in the case of these lesions, the lack of enhancement supports the benign nature of the lesion and may lead to a downgrade of the BI-RADS category.

A population-based survey of self-reported delays in breast, cervical, colorectal and lung cancer screening

The early COVID-19 pandemic was associated with cessation of screening services, but the prevalence of ongoing delays in cancer screening into the third year of the pandemic are not well-characterized. In February/March 2022, a population-based survey assessed cancer needs in New Hampshire and Vermont. The associations between cancer screening delays (breast, cervical, colorectal or lung cancer) and social determinants of health, health care access, and cancer attitudes and beliefs were tested. Distributions and Rao-Scott chi-square tests were used for hypothesis testing and weighted to represent state populations. Of 1717 participants, 55% resided in rural areas, 96% identified as White race, 50% were women, 36% had high school or less education. Screening delays were reported for breast cancer (28%), cervical cancer (30%), colorectal cancer (24%), and lung cancer (30%). Delays were associated with having higher educational attainment (lung), urban living (colorectal), and having Medicaid insurance (breast, cervical). Low confidence in ability to obtain information about cancer was associated with screening delays across screening types. The most common reason for delay was the perception that the screening test was not urgent (31% breast, 30% cervical, 28% colorectal). Cost was the most common reason for delayed lung cancer screening (36%). COVID-19 was indicated as a delay reason in 15-29% of respondents; 12-20% reported health system capacity during the pandemic as a reason for delay, depending on screening type. Interventions that address sub-populations and reasons for screening delays are needed to mitigate the impact of the COVID-19 pandemic on cancer burden and mortality.

Mixed-Method Systematic Review and Meta-Analysis of Shared Decision-Making Tools for Cancer Screening

This review aimed to synthesize evidence on the effectiveness of shared decision-making (SDM) tools for cancer screening and explored the preferences of vulnerable people and clinicians regarding the specific characteristics of the SDM tools. A mixed-method convergent segregated approach was employed, which involved an independent synthesis of quantitative and qualitative data. Articles were systematically selected and screened, resulting in the inclusion and critical appraisal of 55 studies. Results from the meta-analysis revealed that SDM tools were more effective for improving knowledge, reducing decisional conflict, and increasing screening intentions among vulnerable populations compared to non-vulnerable populations. Subgroup analyses showed minimal heterogeneity for decisional conflict outcomes measured over a six-month period. Insights from the qualitative findings revealed the complexities of clinicians' and vulnerable populations' preferences for an SDM tool in cancer screening. Vulnerable populations highly preferred SDM tools with relevant information, culturally tailored content, and appropriate communication strategies. Clinicians, on the other hand, highly preferred tools that can be easily integrated into their medical systems for efficient use and can effectively guide their practice for cancer screening while considering patients' values. Considering the complexities of patients' and clinicians' preferences in SDM tool characteristics, fostering collaboration between patients and clinicians during the creation of an SDM tool for cancer screening is essential. This collaboration may ensure effective communication about the specific tool characteristics that best support the needs and preferences of both parties.

Combination of ultrafast dynamic contrast-enhanced MRI-based radiomics and artificial neural network in assessing BI-RADS 4 breast lesions: Potential to avoid unnecessary biopsies

Objectives

To investigate whether combining radiomics extracted from ultrafast dynamic contrast-enhanced MRI (DCE-MRI) with an artificial neural network enables differentiation of MR BI-RADS 4 breast lesions and thereby avoids false-positive biopsies.

Methods

This retrospective study consecutively included patients with MR BI-RADS 4 lesions. The ultrafast imaging was performed using Differential sub-sampling with cartesian ordering (DISCO) technique and the tenth and fifteenth postcontrast DISCO images (DISCO-10 and DISCO-15) were selected for further analysis. An experienced radiologist used freely available software (FAE) to perform radiomics extraction. After principal component analysis (PCA), a multilayer perceptron artificial neural network (ANN) to distinguish between malignant and benign lesions was developed and tested using a random allocation approach. ROC analysis was performed to evaluate the diagnostic performance.

Results

173 patients (mean age 43.1 years, range 18-69 years) with 182 lesions (95 benign, 87 malignant) were included. Three types of independent principal components were obtained from the radiomics based on DISCO-10, DISCO-15, and their combination, respectively. In the testing dataset, ANN models showed excellent diagnostic performance with AUC values of 0.915-0.956. Applying the high-sensitivity cutoffs identified in the training dataset demonstrated the potential to reduce the number of unnecessary biopsies by 63.33%-83.33% at the price of one false-negative diagnosis within the testing dataset.

Conclusions

The ultrafast DCE-MRI radiomics-based machine learning model could classify MR BI-RADS category 4 lesions into benign or malignant, highlighting its potential for future application as a new tool for clinical diagnosis.

Fully automatic classification of breast lesions on multi-parameter MRI using a radiomics model with minimal number of stable, interpretable features

PURPOSE

To build an automatic computer-aided diagnosis (CAD) pipeline based on multiparametric magnetic resonance imaging (mpMRI) and explore the role of different imaging features in the classification of breast cancer.

MATERIALS AND METHODS

A total of 222 histopathology-confirmed breast lesions, together with their BI-RADS scores, were included in the analysis. The cohort was randomly split into training (159) and test (63) cohorts, and another 50 lesions were collected as an external cohort. An nnUNet-based lesion segmentation model was trained to automatically segment lesion ROI, from which radiomics features were extracted for diffusion-weighted imaging (DWI), T2-weighted imaging (T2WI), and contrast-enhanced (DCE) pharmacokinetic parametric maps. Models based on combinations of sequences were built using support vector machine (SVM) and logistic regression (LR). Also, the performance of these sequence combinations and BI-RADS scores were compared. The Dice coefficient and AUC were calculated  to evaluate the segmentation and classification results. Decision curve analysis (DCA) was used to assess clinical utility.

RESULTS

The segmentation model achieved a Dice coefficient of 0.831 in the test cohort. The radiomics model used only three features from diffusion coefficient (ADC) images, T2WI, and DCE-derived kinetic mapping, and achieved an AUC of 0.946 [0.883-0.990], AUC of 0.842 [0.6856-0.998] in the external cohort, which was higher than the BI-RADS score with an AUC of 0.872 [0.752-0.975]. The joint model using both radiomics score and BI-RADS score achieved the highest test AUC of 0.975 [0.935-1.000], with a sensitivity of 0.920 and a specificity of 0.923.

CONCLUSION

Three radiomics features can be used to construct an automatic radiomics-based pipeline to improve the diagnosis of breast lesions and reduce unnecessary biopsies, especially when using jointly with BI-RADS scores.

Revealing the sources of arsenic in private well water using Random Forest Classification and Regression

Exposure to arsenic through private drinking water wells causes serious human health risks throughout the globe. Water testing data indicates there is arsenic contamination in private drinking water wells across New Jersey. To reduce the adverse health risk due to exposure to arsenic in drinking water, it is necessary to identify arsenic sources affecting private wells. Private wells are not regulated by any federal or state agencies through the Safe Drinking Water Act and therefore information is often lacking. To this end, we have developed machine learning algorithms including Random Forest Classification and Regression to decipher the factors contributing to higher arsenic concentration in private drinking water wells in west-central New Jersey. Arsenic concentration in private drinking water wells served as a response variable while explanatory variables were geological bedrock type, soil type, drainage class, land use/cover, and presence of orchards, contaminated sites, and abandoned mines within the 152.4-meter (500 ft) radius of each well. Random Forest Classification and Regression achieved 66 % and 55 % prediction accuracies for arsenic concentration in private drinking water wells, respectively. Overall, both models identify that bedrock, soil, land use/cover, and drainage type (in descending order) are the most important variables contributing to higher arsenic concentration in well water. These models further identify bedrock subgroups at a finer scale including Passaic Formation, Lockatong Formation, Stockton Formation contributing significantly to arsenic concentration in well water. Identification of sources of arsenic contamination in private drinking water wells at such a fine scale facilitates development of more targeted outreach as well as mitigation strategies to improve water quality and safeguard human health.

Evaluation of the differentiation of benign and malignant breast lesions using synthetic relaxometry and the Kaiser score

Objective

To investigate whether there is added value of quantitative parameters from synthetic magnetic resonance imaging (SyMRI) as a complement to the Kaiser score (KS) to differentiate benign and malignant breast lesions.

Materials and methods

In this single-institution study, 122 patients who underwent breast MRI from March 2020 to May 2021 were retrospectively analyzed. SyMRI and dynamic contrast-enhanced MRI were performed using a 3.0-T system. Two experienced radiologists independently assigned the KS and measured the quantitative values of T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) from SyMRI. Pathology was regarded as the gold standard. The diagnostic values were compared using the appropriate statistical tests.

Results

There were 122 lesions (86 malignant and 36 benign) in 122 women. The T1 value was identified as the only independent factor for the differentiation of malignant and benign lesions. The diagnostic accuracy of incorporating the T1 into the KS protocol (T1+KS) was 95.1% and 92.1% for all lesions (ALL) and The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions, respectively, which was significantly higher than that of either T1 (ALL: 82.8%, P = 0.0001; BI-RADS 4: 78.9%, P = 0.002) or KS (ALL: 90.2%, P = 0.031; BI-RADS 4: 84.2%, P = 0.031) alone. The sensitivity and specificity of T1+KS were also higher than those of the T1 or KS alone. The combined diagnosis could have avoided another 15.6% biopsies compared with using KS alone.

Conclusions

Incorporating T1 into the KS protocol improved both the sensitivity and specificity to differentiate benign and malignant breast lesions, thus avoiding unnecessary invasive procedures.

The circulating tumor DNA (ctDNA) alteration level predicts therapeutic response in metastatic breast cancer: Novel prognostic indexes based on ctDNA

Purpose

Circulating tumor DNA (ctDNA) has good clinical guiding value for metastatic breast cancer (MBC) patients. This study aimed to apply a novel genetic analysis approach for therapeutic prediction based on ctDNA alterations.

Method

This nonrandomized, multicenter study recruited 223 MBC patients (NCT05079074). Plasma samples were collected for target-capture deep sequencing of ctDNA at baseline, after the 2nd cycle of treatment, and when progressive disease (PD) was evaluated. Samples were categorized into four levels according to the number of ctDNA alterations: level 1 (no alterations), level 2 (1–2 alterations), level 3 (3–4 alterations) and level 4 (≥5 alterations). According to ctDNA alteration level and variant allele frequency (VAF), a novel ctDNA-level Response Evaluation Criterion in Solid Tumors (ctle-RECIST) was established to assess treatment response and predict progression-free survival (PFS).

Results

The median PFS in level 1 (6.63 months) patients was significantly longer than that in level 2–4 patients (level 2: 5.70 months; level 3–4: 4.90 months, p < 0.05). After 2 cycles of treatment, based on ctle-RECIST, the median PFS of level-based disease control rate (lev-DCR) patients was significantly longer than that of level-based PD (lev-PD) patients [HR 2.42 (1.52–3.85), p < 0.001]. In addition, we found that ctDNA level assessment could be a good supplement to radiologic assessment. The median PFS in the dual-DCR group tended to be longer than that in the single-DCR group [HR 1.41 (0.93–2.13), p = 0.107].

Conclusion

The ctDNA alteration level and ctle-RECIST could be novel biomarkers of prognosis and could complement radiologic assessment in MBC.

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Based on the number of ctDNA alterations, samples were categorized into four levels: level 1 to level 4.

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ctDNA alterations differed in different alteration level groups.

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Higher ctDNA alteration levels (levels 3–4) were associated with a higher probability of liver metastasis.

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According to ctDNA alteration level and variant allele frequency, a novel ctDNA-level RECIST (ctle-RECIST) was established to assess treatment response.

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ctle-RECIST can not only independently predict PFS, but also assist radiologic assessment and improve the clinical application value of prediction.

Comparison of Cancer Survival Trends in Hungary in the Periods 2001-2005 and 2011-2015 According to a Population-Based Cancer Registry

Background: Assessment of population-based cancer survival may provide the most valuable feedback about the effectiveness of oncological surveillance and treatment. Aims: Based on the database of the Hungarian National Cancer Registry, standardized incidence rates of lung, breast, colorectal, prostate and cervical cancer were compared to standardized mortality data of the Hungarian Central Statistical Office in the period between 2001 and 2015. Then survival analysis was performed on cleansed database. Results: The incidence of colorectal, breast and prostate cancer increased, while standardized rates of lung and cervical cancer declined. The survival of colorectal, breast and prostate cancer showed improvement. Contrarily, lung cancer exhibited a mild decline, while that of cervical cancer did not change significantly. In earlier stages survival was improved among almost every studied tumor type, while in advanced stages improvement was not observed. Comparison of stage distribution revealed that in the 2011-2015 period colorectal, breast and prostate cancer cases were diagnosed at earlier stages, while lung and cervical cancer patients were typically discovered at more advanced stages. Discussion: The outcome of advanced cancer treatments is better in earlier stages, which highlighted the importance of screening network. However, growth of oncological treatment costs with longer patient survival imposes a constantly increasing burden on society.

Satisfaction and its determinants of rural upper gastrointestinal cancer screening in China: a preliminary cross-sectional study

OBJECTIVES

To assess participants' satisfaction with and predictors of upper gastrointestinal cancer screening in rural areas.

DESIGN

Cross-sectional study.

SETTING

Ten screening centres in seven cities across five provinces in China.

PARTICIPANTS

Of the 452 participants screened during the survey period, 438 completed the survey (response rate: 96.90%).

PRIMARY OUTCOME MEASURES

Screening satisfaction was the primary outcome and it was assessed using the Patient Satisfaction Questionnaire-18. Ordinal logistic regression analysis was used to analyse the predictors of satisfaction.

RESULTS

The percentages of satisfaction with the General Satisfaction, Technical Quality, Interpersonal Manner, Communication, Financial Aspects, Time Spent With Doctor, and Convenience and Accessibility dimensions were 95.89%, 79.68%, 88.36%, 83.56%, 75.11%, 82.19% and 66.44%, respectively. Education (OR 0.25, 95% CI 0.07 to 0.90), health self-assessment (OR 15.29, 95% CI 2.86 to 81.78) and family history of cancer (OR 4.20, 95% CI 1.29 to 13.71) were associated with General Satisfaction. Residence (OR 4.31, 95% CI 1.89 to 9.81) was associated with Technical Quality. Occupation (OR 0.27, 95% CI 0.08 to 0.88), health self-assessment (OR 11.30, 95% CI 3.94 to 32.43), screening purpose (OR 0.18, 95% CI 0.03 to 0.92) and distance from the screening centre (OR 4.59, 95% CI 1.35 to 15.61) were associated with interpersonal manner. Gender (OR 1.85, 95% CI 1.02 to 3.34), residence (OR 3.23, 95% CI 1.23 to 8.53) and endoscopy in the previous year (OR 2.79, 95% CI 1.13 to 6.90) were associated with Communication. Body mass index (BMI; OR 5.06, 95% CI 1.40 to 18.25) and health self-assessment (OR 2.09, 95% CI 1.12 to 3.88) were associated with financial aspects. Gender (OR 1.90, 95% CI 1.07 to 3.38), residence (OR 3.19, 95% CI 1.30 to 7.79), BMI (OR 5.26, 95% CI 1.14 to 24.34) and health self-assessment (OR 2.14, 95% CI 1.06 to 4.34) were associated with time spent with doctor. Gender (OR 1.64, 95% CI 1.04 to 2.60) and residence (OR 3.17, 95% CI 1.46 to 6.88) were associated with convenience and accessibility.

CONCLUSION

There was heterogeneity across the dimensions of satisfaction with rural upper gastrointestinal cancer screening. Project manager should prioritise improving the aspects related to the convenience and accessibility dimension. Furthermore, to improve the efficiency of potential interventions, the predictors of the various dimensions should be considered.

Implementation of a Hepatocellular Carcinoma Screening Program for At-risk Patients Safety-Net Hospital: A Model for National Dissemination

OBJECTIVE

This study aimed to enhance hepatocellular carcinoma (HCC) screening to achieve earlier diagnosis of patients with hepatitis C (HCV) cirrhosis in our Safety-Net population.

BACKGROUND

Adherence to HCC screening guidelines at Safety-Net hospitals is poor. Only 23% of patients with HCC at our health system had a screening exam within 1-year of diagnosis and 46% presented with stage IV disease. HCV-induced cirrhosis remains the most common etiology of HCC (75%) in our patients.

METHODS

In the setting of an established HCV treatment clinic, an HCC screening quality improvement initiative was initiated for patients with stage 3 fibrosis or cirrhosis by transient elastography. The program consisted of semiannual imaging. Navigators scheduled imaging appointments and tracked compliance.

RESULTS

From April 2018 to April 2021, 318 patients were enrolled (mean age 61 years, 81% Black race, 38% uninsured). Adherence to screening was higher than previously reported: 94%, 75%, and 74% of patients completed their first, second, and third imaging tests. Twenty-two patients (7%) were diagnosed with HCC; 55% stage I and 14% stage IV. All patients were referred and 13 (59%) received treatment. Median time to receipt of treatment was 77 days (range, 32-282). Median overall survival for treated patients was 32 months.

CONCLUSIONS

Implementation of an HCC screening program at a safety-net hospital is feasible and facilitated earlier diagnosis in this study. Patient navigation and tracking completion of imaging tests were key components of the program's success. Next steps include expanding the program to additional at-risk populations.

Cardiovascular Disease Risk Among Cancer Survivors: The Atherosclerosis Risk In Communities (ARIC) Study

BACKGROUND

More than 80% of adult patients diagnosed with cancer survive long term. Long-term complications of cancer and its therapies may increase the risk of cardiovascular disease (CVD), but prospective studies using adjudicated cancer and CVD events are lacking.

OBJECTIVES

The aim of this study was to assess the risk of CVD in cancer survivors in a prospective community-based study.

METHODS

We included 12,414 ARIC (Atherosclerosis Risk In Communities) study participants. Cancer diagnoses were ascertained via linkage with state registries supplemented with medical records. Incident CVD outcomes were coronary heart disease (CHD), heart failure (HF), stroke, and a composite of these. We used multivariable Poisson and Cox regressions to estimate the association of cancer with incident CVD.

RESULTS

Mean age was 54 years, 55% were female, and 25% were Black. A total of 3,250 participants (25%) had incident cancer over a median 13.6 years of follow-up. Age-adjusted incidence rates of CVD (per 1,000 person-years) were 23.1 (95% CI: 24.7-29.1) for cancer survivors and 12.0 (95% CI: 11.5-12.4) for subjects without cancer. After adjustment for cardiovascular risk factors, cancer survivors had significantly higher risks of CVD (HR: 1.37; 95% CI: 1.26-1.50), HF (HR: 1.52; 95% CI: 1.38-1.68), and stroke (HR: 1.22; 95% CI: 1.03-1.44), but not CHD (HR: 1.11; 95% CI: 0.97-1.28). Breast, lung, colorectal, and hematologic/lymphatic cancers, but not prostate cancer, were significantly associated with CVD risk.

CONCLUSIONS

Compared with persons without cancer, adult cancer survivors have significantly higher risk of CVD, especially HF, independent of traditional cardiovascular risk factors. There is an unmet need to define strategies for CVD prevention in this high-risk population.

Assessing acute myeloid leukemia susceptibility in rearrangement-driven patients by DNA breakage at topoisomerase II and CCCTC-binding factor/cohesin binding sites

An initiating DNA double strand break (DSB) event precedes the formation of cancer-driven chromosomal abnormalities, such as gene rearrangements. Therefore, measuring DNA breaks at rearrangement-participating regions can provide a unique tool to identify and characterize susceptible individuals. Here, we developed a highly sensitive and low-input DNA break mapping method, the first of its kind for patient samples. We then measured genome-wide DNA breakage in normal cells of acute myeloid leukemia (AML) patients with KMT2A (previously MLL) rearrangements, compared to that of nonfusion AML individuals, as a means to evaluate individual susceptibility to gene rearrangements. DNA breakage at the KMT2A gene region was significantly greater in fusion-driven remission individuals, as compared to nonfusion individuals. Moreover, we identified select topoisomerase II (TOP2)-sensitive and CCCTC-binding factor (CTCF)/cohesin-binding sites with preferential DNA breakage in fusion-driven patients. Importantly, measuring DSBs at these sites, in addition to the KMT2A gene region, provided greater predictive power when assessing individual break susceptibility. We also demonstrated that low-dose etoposide exposure further elevated DNA breakage at these regions in fusion-driven AML patients, but not in nonfusion patients, indicating that these sites are preferentially sensitive to TOP2 activity in fusion-driven AML patients. These results support that mapping of DSBs in patients enables discovery of novel break-prone regions and monitoring of individuals susceptible to chromosomal abnormalities, and thus cancer. This will build the foundation for early detection of cancer-susceptible individuals, as well as those preferentially susceptible to therapy-related malignancies caused by treatment with TOP2 poisons.

Value of breast MRI omics features and clinical characteristics in Breast Imaging Reporting and Data System (BI-RADS) category 4 breast lesions: an analysis of radiomics-based diagnosis

Background

The Breast Imaging Reporting and Data System (BI-RADS) category 4 breast lesions is categorized into 4A, 4B, and 4C, which reflect an increasing malignancy potential from low (2–10%) moderate (10–50%) and high (50–95%). Determining the benign and malignant of BI-RADS category 4 breast lesions is very important for accurate diagnosis and follow-up treatment. This study aimed to explore the value of breast magnetic resonance imaging (MRI) omics features and clinical characteristics in the assessment of BI-RADS category 4 breast lesions.

Methods

This retrospective study analyzed 96 lesions (39 benign and 57 malignant) from 92 patients diagnosed with MRI BI-RADS category 4 lesions in the Second Affiliated Hospital of Dalian Medical University between May 2017 and December 2019. The lesions were sub-categorized as BI-RADS 4A, 4B, or 4C based on the MRI findings. An imaging omics analysis model was applied to extract the MRI features. The positive predictive value (PPV) of each subcategory was calculated, and the area under the curve (AUC) was used to describe the efficiency for different diagnoses. Moreover, we analyzed 17 clinical indicators to assess their diagnostic value for BI-RADS category 4 breast lesions.

Results

The PPVs of BI-RADS 4A, 4B, and 4C were 7.1% (2/28), 41.2% (7/17), and 94.1% (48/51), respectively. The AUC, sensitivity, and specificity were 0.919, 84.2%, and 92.3%, respectively. The combination of T₁-weighted images (T₁WI) with dynamic contrast-enhanced (DCE) MRI yielded the best diagnostic results among all dual sequences. Two clinical indicators [progesterone receptor (PR) and Ki-67 expression] achieved an AUC almost equal to 1.0. The radiomics and redundancy reduction methods reduced the clinical data features from 1,233 to 14.

Conclusions

High diagnostic performance can be achieved in distinguishing malignant breast BI-RADS category 4 lesions using the combination of T₁WI and DCE in MRI. Combining the PR and Ki-67 expression variables can further improve MRI accuracy for breast BI-RADS category 4 lesions.

Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine

Over the past decade, artificial intelligence (AI) has contributed substantially to the resolution of various medical problems, including cancer. Deep learning (DL), a subfield of AI, is characterized by its ability to perform automated feature extraction and has great power in the assimilation and evaluation of large amounts of complicated data. On the basis of a large quantity of medical data and novel computational technologies, AI, especially DL, has been applied in various aspects of oncology research and has the potential to enhance cancer diagnosis and treatment. These applications range from early cancer detection, diagnosis, classification and grading, molecular characterization of tumors, prediction of patient outcomes and treatment responses, personalized treatment, automatic radiotherapy workflows, novel anti-cancer drug discovery, and clinical trials. In this review, we introduced the general principle of AI, summarized major areas of its application for cancer diagnosis and treatment, and discussed its future directions and remaining challenges. As the adoption of AI in clinical use is increasing, we anticipate the arrival of AI-powered cancer care.

Tracing the potential of networks to improve community cancer care: an in-depth single case study

Background

Despite overall declines in cancer mortality in the USA over the past three decades, many patients in community settings fail to receive evidence-based cancer care. Networks that link academic medical centers (AMCs) and community providers may reduce disparities by creating access to specialized expertise and care, but research on network effectiveness is mixed. The objective of this study was to identify factors related to whether and how an exemplar AMC network served to provide advice and referral access in community settings.

Methods

An embedded in–depth single case study design was employed to study a network in the Midwest USA that connects a leading cancer specialty AMC with community practices. The embedded case units were a subset of 20 patients with young-onset colorectal cancer or risk-related conditions and the providers involved in their care. The electronic health record (EHR) was reviewed from January 1, 1990, to February 28, 2018. Social network analysis identified care, advice, and referral relationships. Within-case process tracing provided detailed accounts of whether and how the network provided access to expert, evidence-based care or advice in order to identify factors related to network effectiveness.

Results

The network created access to evidence-based advice or care in some but not all case units, and there was variability in whether and how community providers engaged the network, including the path for referrals to the AMC and the way in which advice about an evidence-based approach to care was communicated from AMC specialists to community providers. Factors related to instances when the network functioned as intended included opportunities for both rich and lean communication between community providers and specialists, coordinated referrals, and efficient and adequately utilized documentation systems.

Conclusions

Network existence alone is insufficient to open up access to evidence-based expertise or care for patients in community settings. In-depth understanding of how this network operated provides insight into factors that support or inhibit the potential of networks to minimize disparities in access to evidence-based community cancer care, including both personal and organizational factors.

Pri-miR526b and Pri-miR655 Are Potential Blood Biomarkers for Breast Cancer

Simple Summary

Previously, we reported that the expression of two oncogenic miRNAs, miR526b and miR655, in poorly metastatic breast cancer cells enhances aggressive breast cancer phenotypes. Furthermore, miR526b and miR655 expression in breast tumors is associated with poor patient survival. We recently showed that both miRNAs are major regulators of the tumor microenvironment and can be detected in cell-free tumor cell secretions. Therefore, we wanted to test the biomarker potential of these two miRNAs. Early detection can improve breast cancer patient survival by 98%. Here, we report novel findings that precursors of both miRNAs, pri-miR526b and pri-miR655, are sensitive and robust blood biomarkers to distinguish cancer from benign plasmas. Pri-miR526b proved to be a very sensitive biomarker in detecting breast cancer at an early stage. Hence, pri-miR526b can be used as an early diagnostic biomarker for breast cancer.

Abstract

We reported that two microRNAs, miR526b and miR655, are oncogenic in breast cancer (BC). Overexpression of these two miRNAs in poorly metastatic BC cells promotes aggressive BC phenotypes in vitro and in vivo. High expression of each miRNA was associated with poor patient survival. In this pilot biomarker study, we report for the first time that miRNA precursor RNAs (pri-miRNAs) are robust and sensitive biomarkers for BC, detectable in both human blood plasma and biopsy tissues. Pri-miRNA detection and quantification do not require a special enrichment procedure, thus reducing specimen quantity. Blood plasma samples from 90 malignant tumor-bearing patients and 20 benign lesion-bearing participants (control) were analyzed for pri-miRNA expression with a quantitative real-time polymerase chain reaction. Results revealed that normalized expressions of plasma pri-miR526b and pri-miR655 are significantly upregulated in malignancy compared to benign plasmas (p = 0.002 and p = 0.03, respectively). Both pri-miRNAs showed more prominent results to distinguish stage I plasmas from benign plasmas (p = 0.001 for pri-miR526b and p = 0.0001 for pri-miR655). We have also validated pri-miRNA expression in independent tumor bank tissues, showing significant upregulation of both pri-miRNAs in BC; thus, pri-miRNAs are robust markers. The diagnostic relevance of pri-miRNAs was computed with the area under the curve (AUC). Pri-miR526b is a sensitive biomarker to distinguish cancer from control plasmas (sensitivity of 86%; AUC = 71.47%, p = 0.0027) with a positive predictive value of 88.89%; however, pri-miR655 did not show significant sensitivity. Furthermore, pri-miR526b could also significantly distinguish tumors as early as stage I from control (sensitivity of 75%; AUC = 72.71%, p = 0.0037). Therefore, pri-miR526b can be used as an early diagnostic biomarker. The expression of both pri-miRNAs was significantly high in ER-positive and HER2-negative subgroups of BC; hence, these biomarkers might play a role in the management of endocrine therapy designs. Additionally, with a case–control cohort study, we identified that high expression of pri-miR526b in the blood is also a risk factor associated with breast cancer (OR = 4.3, CI = 1.39–13.34, p = 0.01). Pri-miRNAs could be considered novel breast cancer blood biomarkers.

Challenges in Diversity, Equity, and Inclusion in Research and Clinical Oncology

Disparities are common and well-known in the field of clinical oncology and cancer research. In patient care, poor access and a number of other factors disadvantage patients and this can lead to inadequate screening, prevention or treatment of cancer and poor patient outcomes. World-wide, socioeconomic status, health care expenditures and a number of other challenges contribute to disparities in cancer care and patient outcomes. Access to cancer clinical trials remains inadequate for underrepresented minorities as well as non-white racial and ethnic groups. There are also disparities and many challenges in the biomedical research enterprise that can limit innovation and that must be addressed as part of active interventions.

Lung Cancer Attributed Mortality Among 316,336 Early Stage Breast Cancer Cases Treated by Radiotherapy and/or Chemotherapy, 2000-2015: Evidence From the SEER Database

Objective

To estimate the risk of death from lung cancer in patients treated for breast cancer (BC) in relation to the general population.

Methods

BC data, covering 2000 to 2015, were extracted from the Surveillance, Epidemiology and End Results-18 (SEER-18) cancer registry database. A comparison of lung cancer attributed mortality between BC patients and the general population was performed using standardized mortality ratios (SMRs) and SMRs conditional on survival length (cSMRs). Prognostic factors of lung cancer mortality were identified using flexible parametric modelling. Our model adjusts the effect of downstream (histopathological BC tumor grade and hormone receptor status) and upstream (age at diagnosis, ethnicity, and marital status) factors.

Results

The median follow-up was 6.4 years (interquartile range, 3.0–10.3 years). BC cases who received only radiotherapy (cSMR = 0.93; 95%CI: 0.77–1.13), only chemotherapy (cSMR = 0.91; 0.62–1.33), and radio-and chemotherapy (cSMR = 1.04; 0.77–1.39) had no evidence of increased lung cancer mortality relative to the general population. The adjusted model identified that lung cancer mortality was higher for women who were older at diagnosis compared to those <50 years (ranging from HR50-59 = 3.41 [95%CI: 2.72–4.28] to HR70-79 = 10.53 [95%CI: 8.44–13.13]) and for cases with negative estrogen and progesterone receptors (HR =1.38; 95% CI: 1.21–1.57). Compared to married cases, widowed, divorced, single or others had a 76%, 45%, and 25% higher hazard of lung cancer mortality, respectively. Lung cancer mortality was lower for American Indian/Alaska Native and Asian/Pacific Islander ethnicities (HR = 0.51; 95% CI: 0.40–0.64) compared to BC cases with white ethnic background.

Conclusions

There is no evidence for a higher lung cancer mortality in BC patients when compared to the general population.

Investigation of Synthetic Relaxometry and Diffusion Measures in the Differentiation of Benign and Malignant Breast Lesions as Compared to BI-RADS

BACKGROUND

Breast cancer is the most common malignant tumor in women and a quantitative contrast-free method is highly desirable for its diagnosis.

PURPOSE

To investigate the performance of quantitative MRI in differentiating malignant from benign breast lesions and to compare with the Breast Imaging Reporting and Data System (BI-RADS).

STUDY TYPE

Retrospective.

SUBJECTS

Eighty patients (56 with malignant lesions and 24 with benign lesions).

FIELD STRENGTH/SEQUENCE

Diffusion-weighted imaging (DWI) with a single-shot echo planar sequence and synthetic MRI with magnetic resonance image compilation (MAGiC) were performed at 3T.

ASSESSMENT

T₁ relaxation time (T₁ ), T₂ relaxation time (T₂ ), and proton density (PD) from synthetic MRI and apparent diffusion coefficient (ADC) from DWI were analyzed by two radiologists (Reader A, Reader B). Univariable and multivariable models were developed to optimize differentiation between malignant and benign lesions and their performances compared to BI-RADS.

STATISTICAL TESTS

The diagnostic performance was evaluated using multivariate logistic regression analysis and area under the receiver operating characteristic (ROC) curves (AUC).

RESULTS

T₂ , PD, and ADC values for malignant lesions were significantly lower than those in benign breast lesions for both radiologists (all P < 0.05). The combined T₂ , PD, and ADC model had the best performance for differentiating malignant and benign lesions with AUC, sensitivity, specificity, positive predictive value, and negative predictive values of 0.904, 94.6%, 87.5%, 94.6%, and 87.5%, respectively. The corresponding results for BI-RADS were no AUC, 94.6%, 75.0%, 89.8%, and 85.7%, respectively.

DATA CONCLUSION

The approach that combined synthetic MRI and DWI outperformed BI-RADS in the differential diagnosis of malignant and benign breast lesions and was achieved without contrast agents. This approach may serve as an alternative and effective strategy for the improvement of breast lesion differentiation.

LEVEL OF EVIDENCE

3.

TECHNICAL EFFICACY STAGE

3.

Inherent and modifiable risk factors for peripheral venous catheter failure during cancer treatment: a prospective cohort study

PURPOSE

To identify modifiable and non-modifiable risk factors for peripheral intravenous catheter (PIV) failure among patients requiring intravenous treatment for oncology and haematology conditions.

METHODS

A single-centre prospective cohort study was conducted between October 2017 and February 2019. Adult in-patients requiring a PIV for therapy were prospectively recruited from two cancer units at a tertiary hospital in Queensland, Australia. The primary outcome was a composite of complications leading to PIV failure (local and bloodstream infection; occlusion; infiltration/extravasation; leakage; dislodgement; and/or phlebitis). Secondary outcomes were (i) PIV dwell time; (ii) insertion and (iii) failure of a CVAD; (iv) adverse events; (v) length of hospital stay. Outcomes were investigated using Bayesian multivariable linear regression modelling and survival analysis.

RESULTS

Of 200 participants, 396 PIVs were included. PIV failure incidence was 34.9%; the most common failure type was occlusion/infiltration (n = 74, 18.7%), then dislodgement (n = 33, 8.3%), and phlebitis (n = 30, 7.6%). While several patient and treatment risk factors were significant in univariable modelling, in the final multivariable model, only the use of non-sterile tape (external to the primary dressing) was significantly associated with decreased PIV dislodgement (hazard ratio 0.06, 95% confidence interval 0.01, 0.48; p = 0.008).

CONCLUSION

PIV failure rates among patients receiving cancer treatment are high, the sequelae of which may include delayed treatment and infection. Larger studies on risk factors and interventions to prevent PIV failure in this population are needed; however, the use of secondary securements (such as non-sterile tape) to provide further securement to the primary PIV dressing is particularly important.

TRIAL REGISTRATION

Study methods were registered prospectively with the Australian New Zealand Clinical Trials Registry on the 27^th March 2017 (ACTRN12617000438358); https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372191&isReview=true.

Long Noncoding RNA HOXD-AS1 Promotes the Proliferation, Migration, and Invasion of Colorectal Cancer via the miR-526b-3p/CCND1 Axis

BACKGROUND

Colorectal cancer (CRC) is one of the most common malignancies in the world. It has been reported that the abnormal expression of long noncoding RNA HOXD-AS1 promotes the development of CRC, while the mechanism is still unclear. The aim of this study is to investigate the effects of HOXD-AS1 on proliferation, migration, and invasion in CRC and explore the underlying mechanism.

METHODS

Quantitative real-time polymerase chain reaction was used to detect the expression levels of HOXD-AS1, miR-526b-3p, and cyclin D1 (CCND1) in CRC tissues and cells. Dual-luciferase reporter assay was applied to examine the interaction between miR-526b-3p and HOXD-AS1 or CCND1. In addition, cell proliferation ability was assessed by Cell Counting Kit-8 assay. Cell migration and invasion abilities were determined using transwell assay. Furthermore, Western blot assay was conducted to measure the protein expression of CCND1.

RESULTS

HOXD-AS1 was highly expressed in CRC, and high expression of HOXD-AS1 was related to the poor prognosis of patients with CRC. MiR-526b-3p could be targeted by HOXD-AS1. Function experiment results revealed that miR-526b-3p inhibitor could reverse the suppressive effect of HOXD-AS1 knockdown on the proliferation, migration, and invasion of CRC cells. Moreover, CCND1 was a target of miR-526b-3p, and its overexpression could reverse the inhibitory effect of miR-526b-3p overexpression on the proliferation, migration, and invasion of CRC cells. In addition, CCND1 overexpression reversed the suppressive effect of HOXD-AS1 knockdown on the proliferation, migration, and invasion of CRC.

CONCLUSIONS

HOXD-AS1 upregulated the expression of CCND1 to promote the proliferation, migration, and invasion of CRC through targeting miR-526b-3p. This provided a new theoretical basis for clinical anticancer research of CRC.

Racial and Socioeconomic Disparities in the Delivery of Immunotherapy for Metastatic Melanoma in the United States

Immunotherapy for metastatic melanoma has rapidly expanded, but racial and/or socioeconomic factors often impact the type of therapies delivered for cancer care. This study addressed a crucial public health priority by evaluating disparities in administration of immunotherapy for metastatic melanoma. The National Cancer Database was queried for newly diagnosed metastatic melanoma. Patients were dichotomized based on receipt of immunotherapy based on National Cancer Database coding. Multivariable logistic regression ascertained factors associated with immunotherapy delivery. Subgroup analysis evaluated the interaction between race, insurance status, and income. Secondarily, Cox multivariate and propensity-matched Kaplan-Meier analyses assessed overall survival based on immunotherapy receipt. Of 15,941 patients meeting the selection criteria, 2448 (15.4%) received immunotherapy, and 13,493 (84.6%) did not. Temporal trends showed that utilization of immunotherapy was 8%-12% of patients between 2004 and 2010, with utilization increasing to 29.7% of patients in 2014. Immunotherapy was more likely administered to younger and healthier patients, at academic centers, and in the absence of chemotherapy and brain metastases (P<0.05 for all). African Americans, along with patients with Medicaid and lower incomes were less likely to receive immunotherapy (P<0.05 for all). As expected, immunotherapy was associated with improved overall survival (median 16.3 vs. 8.3 mo, P<0.001). Although immunotherapy for metastatic melanoma is markedly escalating, not all populations experience this rise equally. Because immunotherapy utilization is expected to amplify even further in the future, these public health and economic issues are essential to identify and address appropriately, and have implications on public health policy, pharmaceutical and insurance companies, and value-based oncology. Methods to address these inequalities are also discussed.

High-Yield Methylation Markers for Stool-Based Detection of Colorectal Cancer

BACKGROUND

Many methylation markers associated with colorectal cancer have been reported, but few of them are actually used in clinical practice.

AIMS

This study was designed to identify promising methylation markers for stool-based detection of colorectal cancer.

METHODS

We first tested 324 reported methylated genes in colorectal cancer cell lines. A total of 111 heavily methylated genes were selected for further evaluation with a pilot set of colorectal cancer and adjacent normal tissues. Ten high-yield methylated markers were further studied in 319 tissue samples. Eventually, the four best markers, namely methylated COL4A1, COL4A2, TLX2, and ITGA4, were validated in 240 stool samples. Methylation-specific PCR (MSP) and real-time MSP (qMSP) were employed for methylation detection.

RESULTS

After hierarchical selection, ten differentially methylated genes demonstrated high sensitivity and specificity for the detection of colorectal cancer in tissue. When validated in stool samples, the four with the best performance-COL4A1, COL4A2, TLX2, and ITGA4-were able to detect 82.5-92.5% of colorectal cancers and 41.6-58.4% of adenomas (≥ 1 cm) with specificity of 88.0-96.4%. The best combination, COL4A2 and TLX2, detected 91.3% of CRCs and 51.9% of advanced adenomas in stool with 97.6% specificity.

CONCLUSIONS

Methylated COL4A1, COL4A2, TLX2, and ITGA4 demonstrated high accuracy for the detection of colorectal neoplasms in stool. They are potentially valuable markers for the detection of colorectal cancer.

Racial and Insurance-related Disparities in Delivery of Immunotherapy-type Compounds in the United States

Racial and/or socioeconomic factors affect the type of therapies delivered for non-small cell lung cancer (NSCLC). Given the rapid expansion of immunotherapy for NSCLC, it is a crucial public health priority to evaluate disparities in administration thereof. The National Cancer Database (NCDB) was queried for newly diagnosed metastatic NSCLC. Patients were dichotomized based on receipt of immunotherapy-type compounds (ICs) based on NCDB coding. Multivariable logistic regression ascertained factors associated with IC delivery. Subgroup analysis, performed by univariate logistic regression modeling, evaluated the effect of race while stratifying for insurance type. Of 504,447 patients, 11,420 (2.3%) received ICs, and 493,027 (97.7%) did not. From 2004 to 2012, ≤1% of patients received ICs; however, 4.9% did so in 2013, 6.6% in 2014, and 8.7% in 2015. ICs were more likely administered to younger and healthier patients, those living farther from treating facilities, and in more educated areas (P<0.05 for all). ICs were more often delivered to adenocarcinomas, and patients who received chemotherapy but not radiotherapy (P<0.05 for all). In addition to geographic differences, uninsured and Medicaid populations received ICs less often, along with African Americans. On subgroup analysis, African Americans were less likely to receive ICs even when stratified for Medicare, Medicaid, or private insurances. Because IC utilization is expected to amplify even further going forward, these public health and economic issues are essential to identify and address appropriately, and have implications on pharmaceutical/insurance companies, value-based oncology, and public health policy. Methods to address these inequalities are also discussed.

Deciphering N6-Methyladenosine-Related Genes Signature to Predict Survival in Lung Adenocarcinoma

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death. Among these, lung adenocarcinoma (LUAD) accounts for most cases. Due to the improvement of precision medicine based on molecular characterization, the treatment of LUAD underwent significant changes. With these changes, the prognosis of LUAD becomes diverse. N⁶-methyladenosine (m⁶A) is the most predominant modification in mRNAs, which has been a research hotspot in the field of oncology. Nevertheless, little has been studied to reveal the correlations between the m⁶A-related genes and prognosis in LUAD. Thus, we conducted a comprehensive analysis of m⁶A-related gene expressions in LUAD patients based on The Cancer Genome Atlas (TCGA) database by revealing their relationship with prognosis. Different expressions of the m⁶A-related genes in tumor tissues and non-tumor tissues were confirmed. Furthermore, their relationship with prognosis was studied via Consensus Clustering Analysis, Principal Components Analysis (PCA), and Least Absolute Shrinkage and Selection Operator (LASSO) Regression. Based on the above analyses, a m⁶A-based signature to predict the overall survival (OS) in LUAD was successfully established. Among the 479 cases, we found that most of the m⁶A-related genes were differentially expressed between tumor and non-tumor tissues. Six genes, HNRNPC, METTL3, YTHDC2, KIAA1429, ALKBH5, and YTHDF1 were screened to build a risk scoring signature, which is strongly related to the clinical features pathological stages (p < 0.05), M stages (p < 0.05), T stages (p < 0.05), gender (p = 0.04), and survival outcome (p = 0.02). Multivariate Cox analysis indicated that risk value could be used as an independent prognostic factor, revealing that the m⁶A-related genes signature has great predictive value. Its efficacy was also validated by data from the Gene Expression Omnibus (GEO) database.

Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions

BACKGROUND

MRI-based radiomics has been used to diagnose breast lesions; however, little research combining quantitative pharmacokinetic parameters of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion kurtosis imaging (DKI) exists.

PURPOSE

To develop and validate a multimodal MRI-based radiomics model for the differential diagnosis of benign and malignant breast lesions and analyze the discriminative abilities of different MR sequences.

STUDY TYPE

Retrospective.

POPULATION

In all, 207 female patients with 207 histopathology-confirmed breast lesions (95 benign and 112 malignant) were included in the study. Then 159 patients were assigned to the training group, and 48 patients comprised the validation group.

FIELD STRENGTH/SEQUENCE

T₂ -weighted (T₂ W), T₁ -weighted (T₁ W), diffusion-weighted MR imaging (b-values = 0, 500, 800, and 2000 seconds/mm² ) and quantitative DCE-MRI were performed on a 3.0T MR scanner.

ASSESSMENT

Radiomics features were extracted from T₂ WI, T₁ WI, DKI, apparent diffusion coefficient (ADC) maps, and DCE pharmacokinetic parameter maps in the training set. Models based on each sequence or combinations of sequences were built using a support vector machine (SVM) classifier and used to differentiate benign and malignant breast lesions in the validation set.

STATISTICAL TESTS

Optimal feature selection was performed by Spearman's rank correlation coefficients and the least absolute shrinkage and selection operator algorithm (LASSO). Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the radiomics models in the validation set.

RESULTS

The area under the ROC curve (AUC) of the optimal radiomics model, including T₂ WI, DKI, and quantitative DCE-MRI parameter maps was 0.921, with an accuracy of 0.833. The AUCs of the models based on T₁ WI, T₂ WI, ADC map, DKI, and DCE pharmacokinetic parameter maps were 0.730, 0.791, 0.770, 0.788, and 0.836, respectively.

DATA CONCLUSION

The model based on radiomics features from T₂ WI, DKI, and quantitative DCE pharmacokinetic parameter maps has a high discriminatory ability for benign and malignant breast lesions.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:596-607.

The American Cancer Society 2035 challenge goal on cancer mortality reduction

A summary evaluation of the 2015 American Cancer Society (ACS) challenge goal showed that overall US mortality from all cancers combined declined 26% over the period from 1990 to 2015. Recent research suggests that US cancer mortality can still be lowered considerably by applying known interventions broadly and equitably. The ACS Board of Directors, therefore, commissioned ACS researchers to determine challenge goals for reductions in cancer mortality by 2035. A statistical model was used to estimate the average annual percent decline in overall cancer death rates among the US general population and among college-educated Americans during the most recent period. Then, the average annual percent decline in the overall cancer death rates of college graduates was applied to the death rates in the general population to project future rates in the United States beginning in 2020. If overall cancer death rates from 2020 through 2035 nationally decline at the pace of those of college graduates, then death rates in 2035 in the United States will drop by 38.3% from the 2015 level and by 54.4% from the 1990 level. On the basis of these results, the ACS 2035 challenge goal was set as a 40% reduction from the 2015 level. Achieving this goal could lead to approximately 1.3 million fewer cancer deaths than would have occurred from 2020 through 2035 and 122,500 fewer cancer deaths in 2035 alone. The results also show that reducing the prevalence of risk factors and achieving optimal adherence to evidence-based screening guidelines by 2025 could lead to a 33.5% reduction in the overall cancer death rate by 2035, attaining 85% of the challenge goal.

Contribution of Breast Cancer to Overall Mortality for US Women

OBJECTIVE

Breast cancer simulation models must take changing mortality rates into account to evaluate the potential impact of cancer control interventions. We estimated mortality rates due to breast cancer and all other causes combined to determine their impact on overall mortality by year, age, and birth cohort.

METHODS

Based on mortality rates from publicly available datasets, an age-period-cohort model was used to estimate the proportion of deaths due to breast cancer for US women aged 0 to 119 years, with birth years 1900 to 2000. Breast cancer mortality was calculated as all-cause mortality multiplied by the proportion of deaths due to breast cancer; other-cause mortality was the difference between all-cause and breast cancer mortality.

RESULTS

Breast cancer and other-cause mortality rates were higher for older ages and birth cohorts. The percent of deaths due to breast cancer increased across birth cohorts from 1900 to 1940 then decreased. Among 50-year-old women, in the 1920 birth cohort, 52 (9.9%) of 100,000 deaths (95% CI, 9.8% to 10.1%) were attributed to breast cancer whereas 476 of 100,000 were due to other causes; in the 1960 birth cohort, 22 (8.5%) of 100,000 deaths (95% CI, 8.3% to 8.7%) were attributed to breast cancer with 242 of 100,000 deaths due to other causes. The percentage of all deaths due to breast cancer was highest (4.1% to 12.9%) for women in their 40s and 50s for all birth cohorts.

CONCLUSIONS

This study offers evidence that advances in breast cancer screening and treatment have reduced breast cancer mortality for women across the age spectrum, and provides estimates of age-, year- and birth cohort-specific competing mortality rates for simulation models. Other-cause mortality estimates are important in these models because most women die from causes other than breast cancer.

Cardiovascular disease-related chronic conditions among Veterans Affairs nonmetastatic colorectal cancer survivors: a matched case-control analysis

Purpose

The growing number of colorectal cancer (CRC) survivors often have multiple chronic conditions. Comparing nonmetastatic CRC survivors and matched noncancer controls, our objectives were to determine the odds of CRC survivors being diagnosed with cardiovascular disease (CVD)-related chronic conditions and their likelihood of control during the year after CRC diagnosis.

Patients and methods

We retrospectively identified patients diagnosed with nonmetastatic CRC in the Veterans Affairs health care system from fiscal years 2009 to 2012 and matched each with up to 3 noncancer control patients. We used logistic regression to assess differences in the likelihood of being diagnosed with CVD-related chronic conditions and control between nonmetastatic CRC survivors and noncancer controls.

Results

We identified 9,758 nonmetastatic CRC patients and matched them to 29,066 noncancer controls. At baseline, 69.4% of CRC survivors and their matched controls were diagnosed with hypertension, 52.4% with hyperlipidemia, and 36.7% with diabetes. Compared to matched noncancer controls, CRC survivors had 57% higher odds of being diagnosed with hypertension (OR=1.57, 95% CI=1.49–1.64) and 7% higher odds of controlled blood pressure (OR=1.07, 95% CI 1.02, 1.13) in the subsequent year. Compared to matched noncancer control patients, CRC survivors had half the odds of being diagnosed with hyperlipidemia (OR=0.50, 95% CI=0.48–0.52) and lower odds of low-density lipoprotein (LDL) control (OR 0.88, 95% CI 0.81–0.94). There were no significant differences between groups for diabetes diagnoses or control.

Conclusion

Compared to noncancer controls, nonmetastatic CRC survivors have 1) greater likelihood of being diagnosed with hypertension and worse blood pressure control in the year following diagnosis; 2) lower likelihood of being diagnosed with hyperlipidemia or LDL control; and 3) comparable diabetes diagnoses and control. There may be a need for hypertension control interventions targeting cancer survivors.

Hybrid volumetric modulated arc therapy for whole breast irradiation: a dosimetric comparison of different arc designs

PURPOSE

To find an optimal arc design for hybrid volumetric modulated arc therapy (H-VMAT), a combination of conventional 3DCRT and VMAT plans for left-sided whole breast radiation therapy.

METHODS AND MATERIALS

A total of 26 left-sided early-stage breast cancer patients were selected for this study. To find the superior plan, H-VMAT with three different arc designs including, two partial arcs (2A), four partial arcs (4A) and four tangential arcs (TA) were created for each study case by combining 3DCRT and VMAT with 75% 3DCRT/25% VMAT dose proportion of prescription dose.

RESULTS

All H-VMAT plans achieved the expected target coverage. A higher conformity index and homogeneity index were achieved for 2A and 4A H-VMAT plans and significantly differ from TA H-VMAT (p < 0.003). The heart and ipsilateral lung dose parameters were comparable among all plans except heart V_40Gy which was significantly less in 4A H-VMAT plan (p < 0.05). The contralateral lung, contralateral breast, spinal cord, normal tissue doses and MU were significantly less in TA H-VMAT (p < 0.03). The beam-on time was significantly less in 2A H-VMAT (p < 0.0001).

CONCLUSION

2A and 4A H-VMAT techniques are effective in improving the PTV dosimetric parameters as well as reducing the OAR doses. Further, 2A H-VMAT delivers less MU and beam-on time compared to 4A H-VMAT.

Clinical utility of quantitative dual-energy CT iodine maps and CT morphological features in distinguishing small-cell from non-small-cell lung cancer

AIM

To evaluate the clinical usefulness of quantitative dual-energy (DE) computed tomography (CT) iodine enhancement metrics combined with morphological CT features in distinguishing small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

One hundred and six untreated lung cancer patients who underwent DECT before biopsy or surgery were prospectively enrolled. Twenty-seven routine CT descriptors, including tumour location, size, shape, margin, enhancement heterogeneity, and internal and surrounding structures, and associated findings were assessed and DECT parameters were measured in all patients. Multiple logistic regression analyses were applied to identify independent predictors of SCLC. The area under the receiver operating characteristic curve was compared between CT features combined with DECT metrics and CT features alone for distinguishing SCLC from NSCLC.

RESULTS

Histology revealed NSCLC in 80 and SCLC in 26 patients. In univariate analysis, 12 morphological CT features and two DECT metrics differed significantly between NSCLC and SCLC. When DECT parameters were combined with CT features for multivariate analysis, the independent predictors of SCLC were large tumour size, central location, confluent mediastinal lymphadenopathy, homogeneous enhancement, absence of coarse spiculation, and lower iodine density and iodine ratio (all p<0.05). The area under the receiver operating characteristic curve was improved from 0.908 to 0.981 after adding DECT metrics compared with CT features alone (p=0.007).

CONCLUSION

The combination of DECT measures and CT morphological features can be used to distinguish SCLC from NSCLC, with higher diagnostic performance compared with CT morphological features alone.

Comparison of Performance Between a Short Categorized Lifestyle Exposure-based Colon Cancer Risk Prediction Tool and a Model Using Continuous Measures

Risk prediction models that estimate an individual's risk of developing colon cancer could be used for a variety of clinical and public health interventions, including offering high-risk individuals enhanced screening or lifestyle interventions. However, if risk prediction models are to be translated into actual clinical and public health practice, they must not only be valid and reliable, but also be easy to use. One way of accomplishing this might be to simplify the information that users of risk prediction tools have to enter, but it is critical to ensure no resulting detrimental effects on model performance. We compared the performance of a simplified, largely categorized exposure-based colon cancer risk model against a more complex, largely continuous exposure-based risk model using two prospective cohorts. Using data from the Nurses' Health Study and the Health Professionals Follow-up Study we included 816 incident colon cancer cases in women and 412 in men. The discrimination of models was not significantly different comparing a categorized risk prediction model with a continuous prediction model in women (c-statistic 0.600 vs. 0.609, P _diff = 0.07) and men (c-statistic 0.622 vs. 0.618, P _diff = 0.60). Both models had good calibration in men [observed case count/expected case count (O/E) = 1.05, P > 0.05] but not in women (O/E = 1.19, P < 0.01). Risk reclassification was slightly improved using categorized predictors in men [net reclassification index (NRI) = 0.041] and slightly worsened in women (NRI = -0.065). Categorical assessment of predictor variables may facilitate use of risk assessment tools in the general population without significant loss of performance.

Problems to affect long-term survival for breast cancer patients: An observational study of subsequent lung/bronchus malignancies

The overall survival of breast cancer (BC) patients increased significantly for decades; however, their long-term survival was seriously impaired by subsequent malignancies. This study aimed to investigate the risk factors of subsequent lung / bronchus primary malignancies among BC survivors.A total of 535,941 BC female survivors diagnosed were identified by using SEERStat database in 1973 to 2014. Among them, 9398 had subsequent lung/bronchus malignancies. Clinico-pathological risk factors were evaluated for the development of subsequent lung/bronchus cancer. The main measures were the incidence and risk factors of subsequent lung/bronchus primaries. Logistic regression analysis and survival analysis were performed.Overall, among 535,941 BC survivors, 73,394 (13.69%) patients with subsequent primaries were identified from 1973 to 2014. The overall medium second tumor-free time was 72 months. Estrogen receptor (ER)-positive, progesterone receptor (PR)-positive, human epidermal growth factor receptor-2 (HER2)-positive, radiotherapy, and surgery treatment were protective factors against overall subsequent malignancies, whereas HER2/hormone receptor (HR) subtype triple negative, increasing tumor size, low differentiation grade, and high TNM stage were risk factors associated with overall subsequent malignancies. Surgical implantation reconstruction was risk factor for lung/bronchus cancer. Even though BC patients had a favorite 5-year survival, their long-term survival was affected by subsequent malignancies, especially for lung/bronchus cancer with high mortality.Nearly 13% BC survivors suffered from subsequent malignancies. Increased risk was related to HER2/HR triple negative and advanced TNM stages. Radiotherapy and surgery were protective factors. Our findings may inform the subsequent cancer counseling of female BC survivors.

A Social-Ecological Review of Cancer Disparities in Kentucky

Cancer continuously ranks among the top 10 leading causes of death in the United States. The burden of cancer is particularly elevated in the Commonwealth of Kentucky and its 54-county Appalachian region, where cancer is the leading cause of death. Kentucky's high rates of cancer have been attributed to a wide range of socioeconomic, behavioral, environmental, and policy influences, resulting in numerous disparities. The present review specifically evaluates the burden of lung, colorectal, cervical, and head and neck cancers in Kentucky, along with resultant cancer control research and community outreach efforts conducted by the state's only National Cancer Institute-designated cancer center using an adapted version of McLeroy's Social-Ecological Model. Here, we categorize disparities and identify relevant intervention approaches based on their level of influence (ie, individual, community, and policy).

Shared Decision-Making and Women's Adherence to Breast and Cervical Cancer Screenings

We examined the effect of shared decision-making (SDM) on women’s adherence to breast and cervical cancer screenings and estimated the prevalence and adherence rate of screenings. The study used a descriptive cross-sectional design using the 2017 Health Information National Trends Survey (HINTS) data collected by the National Cancer Institute. Adherence was defined based on the guidelines from the American Cancer Society and the composite measure of shared decision-making was constructed using three items in the data. Multivariable logistic regression was performed to examine the association between the SDM and adherence, controlling for cancer beliefs and socio-demographic variables. The analysis included 742 responses. Weighted to represent the U.S. population, 68.1% adhered to both breast and cervical cancer screening guidelines. The composite measure of SDM was reliable (α = 0.85), and a higher SDM score was associated with women’s screening adherence (b = 0.17; p = 0.009). There were still women who did not receive cancer screenings as recommended. The results suggest that the use of the SDM approach for healthcare professionals’ communication with patients can improve screening adherence.

Correlation between lung cancer and the HHIP polymorphisms of chronic obstructive pulmonary disease (COPD) in the Chinese Han population

To further investigate the relationship between lung cancer and hedgehog interacting protein (HHIP) polymorphisms of chronic obstructive pulmonary disease (COPD) patients, we conducted a case-control study in a Chinese Han population. Six HHIP SNPs with minor allele frequencies >5% (rs1489758, rs1489759, rs10519717, rs13131837, rs1492820, and rs7689420) were analyzed in 1,017 COPD patients (767 males and 246 females) and 430 non-COPD patients. Using logistic regression analysis, we found that rs7689420 was significantly associated with lung cancer in COPD patients in the Chinese Han population (P < 0.001). The recessive allele of rs7689420 was associated with the occurrence of lung cancer in all COPD patients (odds ratios [OR] of 0.609 and 0.424 for the CT and TT genotypes, respectively) as well as in serious COPD patients (OR of 0.403 and 0.305 for CT and TT, respectively). Additionally, rs1489759 and rs3131837 were associated with lung cancer in various genetic models. rs1489758, rs1489759, and rs10519717 were also associated with lung cancer in serious COPD patients. However, none of the SNPs were significantly associated with lung cancer in mild COPD patients or healthy subjects. Therefore, the HHIP SNPs of COPD patients likely play a role in lung cancer pathology in the Chinese Han population.

Identifying Circulating Tumor DNA Mutation Profiles in Metastatic Breast Cancer Patients with Multiline Resistance

Purpose

In cancer patients, tumor gene mutations contribute to drug resistance and treatment failure. In patients with metastatic breast cancer (MBC), these mutations increase after multiline treatment, thereby decreasing treatment efficiency. The aim of this study was to evaluate gene mutation patterns in MBC patients to predict drug resistance and disease progression.

Method

A total of 68 MBC patients who had received multiline treatment were recruited. Circulating tumor DNA (ctDNA) mutations were evaluated and compared among hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) subgroups.

Results

The baseline gene mutation pattern (at the time of recruitment) varied among HR/HER2 subtypes. BRCA1 and MED12 were frequently mutated in triple negative breast cancer (TNBC) patients, PIK3CA and FAT1 mutations were frequent in HR+ patients, and PIK3CA and ERBB2 mutations were frequent in HER2+ patients. Gene mutation patterns also varied in patients who progressed within either 3 months or 3–6 months of chemotherapy treatment. For example, in HR+ patients who progressed within 3 months of treatment, the frequency of TERT mutations significantly increased. Other related mutations included FAT1 and NOTCH4. In HR+ patients who progressed within 3–6 months, PIK3CA, TP53, MLL3, ERBB2, NOTCH2, and ERS1 were the candidate mutations. This suggests that different mechanisms underlie disease progression at different times after treatment initiation. In the COX model, the ctDNA TP53 + PIK3CA gene mutation pattern successfully predicted progression within 6 months.

Conclusion

ctDNA gene mutation profiles differed among HR/HER2 subtypes of MBC patients. By identifying mutations associated with treatment resistance, we hope to improve therapy selection for MBC patients who received multiline treatment.

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Doctors felt difficult to design effective regimen for MBC patients after multi-line treatment.

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ctDNA testing provide potential treatment targets and reflect treatment response of tumors.

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ctDNA gene mutation pattern varies among four HR/HER2 subgroups.

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The gene mutation patterns also varied between resistant patients and sensitive patients.

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In COX model, ctDNA gene mutation pattern could successfully predict progression within 6 months.

In this study, we clarified the baseline ctDNA mutation pattern for metastatic breast cancer patients. We also selected out treatment-resistance related mutations by ctDNA testing. Here, we showed that PIK3CA were significantly related to HR+.

Moreover, in this study, we also showed a plenty of other rare mutations, including DDR2, CDK12, etc. For different HR/HER2 subtypes, MED12 was frequent in TNBC samples, FAT1 was frequent in HR+ samples, and DDR2 was frequent in HER2+ samples. These findings need further intensive investigations in larger samples.

Accelerating the Pace of Cancer Prevention- Right Now

As a nation, we underinvest in prevention and fail to implement strategies that ensure all population groups equitably share in the return on investment in prevention research and the benefits of prevention effectiveness. There is significant evidence indicating that by applying knowledge that we already have to reduce tobacco, inactivity, and obesity (known modifiable causes of cancer), we can prevent more than 50% of cancers. Vaccination against HPV, aspirin and selective estrogen receptor modulators, and screening programs further reduce risk. Evidence-based prevention strategies are inconsistently implemented across the United States. Substantial variation across States indicates that there is much room for improvement in implementation of prevention. Implementation science applies innovative approaches to identifying, understanding, and developing strategies for overcoming barriers to the adoption, adaptation, integration, scale-up, and sustainability of evidence-based interventions, tools, policies, and guidelines that will prevent cancer through application of evidence-based interventions. When we get implementation of prevention programs right and at scale, we achieve substantial population benefits. Although many efforts are underway to maximize our knowledge about the causes and treatments of cancer, we can achieve reductions in the cancer burden right now by doing what we already know. The time to start is now. Cancer Prev Res; 11(4); 171-84. ©2018 AACR.