Individual- and neighborhood-level predictors of mortality in Florida colorectal cancer patients

Mortality rate and predictors of colorectal cancer patients in Ethiopia: a systematic review and meta-analysis

INTRODUCTION

The incidence of colorectal cancer (CRC) has been increasing in Sub-Saharan countries, including Ethiopia. However, the real mortality rate for CRC patients in Ethiopia has not been established. Therefore, this systematic review and meta-analysis aimed to determine the overall mortality rate and identify predictors among CRC patients in Ethiopia.

METHODS

PubMed, EMBASE, Web of Science, Scopus, Science Direct, and Google Scholar were searched to identify relevant articles. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) were followed. The quality of the included studies was assessed using the Newcastle-Ottawa Scale Critical Appraisal checklist. A random effect model was used to estimate the pooled mortality rate and adjusted hazard ratio (AHR). Publication bias was assessed using funnel plots and Egger's regression test, while heterogeneity was evaluated through the Cochran Q test and I2 statistics.

RESULTS

After reviewing 74 articles, only 7 studies met the criteria and were included in the analysis. The analysis revealed that the overall mortality rate among CRC patients in Ethiopia was 40.5% (95% confidence interval [CI]: 32.05, 48.87) while the survival rates at 1 year, 3 years, and 5 years were 82.3% (95% CI: 73.33, 91.31), 48.8% (95% CI: 43.35, 54.32), and 26.6% (95% CI: 21.26, 31.91) respectively. Subgroup analysis indicated that studies conducted after 2017 had higher mortality rates compared to those studied earlier (43.0% vs. 38.2%). Older age (AHR: 1.89, 95% CI: 1.27, 2.82); being married (AHR: 2.53, 95% CI: 1.79, 3.57); having comorbidities (AHR: 1.84, 95% CI: 1.45, 2.35); having high CEA levels (AHR: 2.06, CI: 1.35, 3.13); being in stage II (AHR: 4.13, 95% CI: 1.85, 9.22), III (AHR: 8.62, 95% CI: 3.88, 19.15), and IV (AHR: 8.06, CI: 2.89, 22.49) were the most important predictors.

CONCLUSION

In Ethiopia, the mortality rate among individuals diagnosed with CRC is high, with two out of five patients dying from this disease. Age, marital status, CEA level, comorbidities, and cancer stage were identified as predictors of mortality in CRC patients. Therefore, early detection and screening should be prioritized, particularly for older patients, those who are married, have comorbidities, elevated CEA levels, and advanced cancer stages.

Environmental Levels of Volatile Organic Compounds, Race, and Socioeconomic Markers Correlate with Areas of High Colorectal Cancer Incidence

BACKGROUND

Ambient levels of volatile organic compounds (VOCs) released from nearby industrial plants have shown positive associations with increased colorectal cancer (CRC) rates. The objective of this study is to analyze the distribution of CRC in the context of socioeconomic status and its correlation with community environmental data.

METHODS

A retrospective study analyzed CRC patients from 2021 to 2023. The census tracts of the patients' residential addresses were obtained, and CRC rates were calculated for each census tract. Socioeconomic data was gathered on these communities. Environmental VOC measurements were obtained from the National Scale Air Toxics Assessment. All datapoints were compared to statewide levels.

RESULTS

Three census tracts in the county had higher CRC cases comparatively. These areas exhibited higher incidence rates and localized clusters of CRC cases, higher distribution of Black or African Americans, lower household incomes, lower home values, and lower educational attainment. VOC measurements in these census tracts had higher levels compared to county and state averages: specifically, 10.68% higher than county and 48.07% higher than state benzene levels (0.52 µg/m3 clusters vs 0.47µg/m3 county vs 0.35 µg/m3 state), 10.84% and 129.15% higher toluene (1.65 µg/m3 vs 1.49 vs 0.72 µg/m3), and 15.64% and 141.87% higher butadiene (0.048 µg/m3 vs 0.041 µg/m3 vs 0.020 µg/m3).

CONCLUSION

This study illustrates a positive correlation between higher ambient exposure to VOCs with increased CRC incidence. These findings underscore the potential interplay of environmental factors, socioeconomic determinants, and environmental injustice when considering strategies to address health disparities and CRC incidence.

Spatial mapping of colorectal cancer screening uptake and associated factors

OBJECTIVE

Over the past decades, it has been understood that the availability of screening tests has contributed to a steady decline in incidence of colorectal cancer (CRC). However, it is also seen that there is a geographic disparity in the use of such tests across small areas. The aim of this study is to examine small-area level barrier factors that may impact CRC screening uptake and to delineate coldspot (low uptake of screening) counties in Florida.

METHODS

Data on the percentages of county-level CRC screening uptakes in 2016 and county-level barrier factors for screening were obtained from the Florida Department of Health, Division of Public Health Statistics & Performance Management. Bayesian spatial beta models were used to produce posterior probability of deceedance to identify coldspots for CRC screening rates.

RESULTS

Unadjusted screening rates using sigmoidoscopy or colonoscopy test ranged from 56.8 to 85%. Bayesian spatial beta models were fitted to the proportion data. At an ecological level, we found that an increasing rate of CRC screening uptake for either of the test types (colon/rectum exam, stool-based test) was strongly associated with a higher health insurance coverage, and lower percentage of population that speak English less than very well (immigration) at county level. Eleven coldspot counties out of 67 total were also identified.

CONCLUSION

This study suggests that health insurance disparities in the use of CRC screening tests are an important factor that may need more attention for resource allocation and health policy targeting small areas with low uptake of screening.

The impact of socioeconomic status on survival in stage III colon cancer patients: A retrospective cohort study using the SEER census-tract dataset

Background

The impact of socioeconomic status (SES) has been described for screening and accessing treatment for colon cancer. However, little is known about the “downstream” effect in patients who receive guideline‐concordant treatment. This study assessed the impact of SES on cancer‐specific survival (CSS) and overall survival (OS) for stage III colon cancer patients.

Methods

The SEER Census Tract‐Level SES Dataset from 2004 to 2015 was used to identify stage III colon adenocarcinoma patients who received curative‐intent surgery and adjuvant chemotherapy. The predictor variable was census tract SES. SES was analyzed as quintiles. The outcome variables were OR and CSS. Statistical analysis included chi square tests for association, Kaplan–Meier, Cox, Fine and Gray regression for survival analysis.

Results

In total, 27,222 patients met inclusion criteria. Lower SES was associated with younger age, Black or Hispanic race/ethnicity, Medicaid/uninsured, higher T stage, and lower grade tumors. CSS at the 25th percentile was 54 months for the lowest SES quintile and 80 for the highest. Median OS was 113 months for the lowest SES quintile and not reached for highest. The 5‐year CSS rate was 72.4% for the lowest SES quintile compared to 78.9% in the highest (p < 0.001). The 5‐year OS rate was 66.5% for the lowest SES quintile and 74.6% in the highest (p < 0.001).

Conclusion

This is the first study to evaluate CSS and OS in an incidence‐based cohort of stage III colon cancer patients using a granular, standardized measure of SES. Despite receipt of guideline‐based treatment, SES was associated with disparities in CSS and OS.

Effect of Neighborhood and Individual-Level Socioeconomic Factors on Colorectal Cancer Screening Adherence

Despite the effectiveness of screenings in reducing colorectal cancer (CRC) mortality, ~25% of US adults do not adhere to screening guidelines. Prior studies associate socioeconomic status (SES) with low screening adherence and suggest that neighborhood deprivation can influence CRC outcomes. We comprehensively investigated the effect of neighborhood SES circumstances (nSES), individual SES, and race/ethnicity on adherence to CRC screening in a multiethnic cross-sectional study. Participant surveys assessing 32 individual-level socioeconomic and healthcare access measures were administered from 2017 to 2018. Participant data were joined with nine nSES measures from the US Census at the census tract level. Univariate, LASSO, and multivariable mixed-effect logistic regression models were used for variable reduction and evaluation of associations. The total study population included 526 participants aged 50–85; 29% of participants were non-adherent. In the final multivariable model, age (p = 0.02) and Non-Hispanic Black race (p = 0.02) were associated with higher odds of adherence. Factors associated with lower adherence were home rental (vs. ownership) (p = 0.003), perception of low healthcare quality (p = 0.006), no routine checkup within two years (p = 0.002), perceived discrimination (p = 0.02), and nSES deprivation (p = 0.02). After comprehensive variable methods were applied, socioeconomic indicators at the neighborhood and individual level were found to contribute to low CRC screening adherence.

Variable selection in social-environmental data: sparse regression and tree ensemble machine learning approaches

Background

Social-environmental data obtained from the US Census is an important resource for understanding health disparities, but rarely is the full dataset utilized for analysis. A barrier to incorporating the full data is a lack of solid recommendations for variable selection, with researchers often hand-selecting a few variables. Thus, we evaluated the ability of empirical machine learning approaches to identify social-environmental factors having a true association with a health outcome.

Methods

We compared several popular machine learning methods, including penalized regressions (e.g. lasso, elastic net), and tree ensemble methods. Via simulation, we assessed the methods’ ability to identify census variables truly associated with binary and continuous outcomes while minimizing false positive results (10 true associations, 1000 total variables). We applied the most promising method to the full census data (p = 14,663 variables) linked to prostate cancer registry data (n = 76,186 cases) to identify social-environmental factors associated with advanced prostate cancer.

Results

In simulations, we found that elastic net identified many true-positive variables, while lasso provided good control of false positives. Using a combined measure of accuracy, hierarchical clustering based on Spearman’s correlation with sparse group lasso regression performed the best overall. Bayesian Adaptive Regression Trees outperformed other tree ensemble methods, but not the sparse group lasso. In the full dataset, the sparse group lasso successfully identified a subset of variables, three of which replicated earlier findings.

Conclusions

This analysis demonstrated the potential of empirical machine learning approaches to identify a small subset of census variables having a true association with the outcome, and that replicate across empiric methods. Sparse clustered regression models performed best, as they identified many true positive variables while controlling false positive discoveries.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-020-01183-9.

The effect of neighborhood social environment on prostate cancer development in black and white men at high risk for prostate cancer

INTRODUCTION

Neighborhood socioeconomic (nSES) factors have been implicated in prostate cancer (PCa) disparities. In line with the Precision Medicine Initiative that suggests clinical and socioenvironmental factors can impact PCa outcomes, we determined whether nSES variables are associated with time to PCa diagnosis and could inform PCa clinical risk assessment.

MATERIALS AND METHODS

The study sample included 358 high risk men (PCa family history and/or Black race), aged 35-69 years, enrolled in an early detection program. Patient variables were linked to 78 nSES variables (employment, income, etc.) from previous literature via geocoding. Patient-level models, including baseline age, prostate specific antigen (PSA), digital rectal exam, as well as combined models (patient plus nSES variables) by race/PCa family history subgroups were built after variable reduction methods using Cox regression and LASSO machine-learning. Model fit of patient and combined models (AIC) were compared; p-values<0.05 were significant. Model-based high/low nSES exposure scores were calculated and the 5-year predicted probability of PCa was plotted against PSA by high/low neighborhood score to preliminarily assess clinical relevance.

RESULTS

In combined models, nSES variables were significantly associated with time to PCa diagnosis. Workers mode of transportation and low income were significant in White men with a PCa family history. Homeownership (%owner-occupied houses with >3 bedrooms) and unemployment were significant in Black men with and without a PCa family history, respectively. The 5-year predicted probability of PCa was higher in men with a high neighborhood score (weighted combination of significant nSES variables) compared to a low score (e.g., Baseline PSA level of 4ng/mL for men with PCa family history: White-26.7% vs 7.7%; Black-56.2% vs 29.7%).

DISCUSSION

Utilizing neighborhood data during patient risk assessment may be useful for high risk men affected by disparities. However, future studies with larger samples and validation/replication steps are needed.

Social determinants of colorectal cancer risk, stage, and survival: a systematic review

BACKGROUND

Several social determinants of health have been examined in relation to colorectal cancer incidence, stage at diagnosis, and survival including income, education, neighborhood disadvantage, immigration status, social support, and social network. Colorectal cancer incidence rates are positively associated with income and other measures of socioeconomic status. In contrast, low socioeconomic status tends to be associated with poorer survival.

METHODS

The present review is based upon bibliographic searches in PubMed and CINAHL and relevant search terms. Articles published in English from 1970 through April 1, 2019 were identified using the following MeSH search terms and Boolean algebra commands: colorectal cancer AND (incidence OR stage OR mortality) AND (social determinants OR neighborhood disadvantage OR racial discrimination OR immigration OR social support).

RESULTS

This review indicates that poverty, lack of education, immigration status, lack of social support, and social isolation play important roles in colorectal cancer stage at diagnosis and survival.

CONCLUSIONS

To address social determinants of colorectal cancer, effective interventions are needed that account for the social contexts in which patients live.

Survival Status and Predictors of Mortality Among Colorectal Cancer Patients in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia: A Retrospective Followup Study

Colorectal cancer is one of the commonest cancer types that has a great public health impact both in developed and developing countries. However, in Ethiopia, the survival status of colorectal cancer patients was not well understood. Therefore, the aim of this study was to determine the survival status and predictors of mortality among colorectal cancer patients in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia in 2019. The institution-based retrospective follow-up study was conducted with 621 subjects who were selected from patients registered between January 1, 2013 and December 30, 2017 with follow-up until December 30th, 2018. Data were collected from patient record review charts. A Kaplan-Meier analysis with a log-rank test, and bivariate and multivariable analysis using the Cox proportional hazard model were used. Of the 621 colorectal cancer patients who were included in the analysis, 202 (32.5%) died. The overall mortality rate was 20.3% per year (95% CI: 17.7-23.3). The overall survival was 18.1% with median survival time of 34.8 months (95% CI: 30.4-36.8). Comorbidity (adjusted hazard ratio [AHR] = 1.8, 95% CI: 1.3-2.5); stage (II [AHR = 3.8, 95% CI: 1.3-11.1], III [AHR = 8.0, 95% CI: 2.8-23.3], IV [AHR = 17.6, 95% CI: 6.1-50.7]); smoking (AHR = 1.6, 95% CI: 1.1-2.3); alcohol consumption (AHR = 1.5, 95% CI: 1.07-2.2); age ≥ 70 (AHR = 1.7, 95% CI: 1.02-2.9); and marital status (married [AHR = 2.4, 95% CI: 1.5-3.8], widowed [AHR = 2.4, 95% CI: 1.2-4.6], divorced [AHR = 2.0, 95% CI: 1.1-3.7]) were significant predictors of colorectal cancer mortality. It is crucial to implement early detection and screening, giving priority to rural dweller, comorbid patients and advanced stage diagnosed patients.

Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review

Background

Nonclinical determinants of health are of increasing importance to health care delivery and health policy. Concurrent with growing interest in better addressing patients’ nonmedical issues is the exponential growth in availability of data sources that provide insight into these nonclinical determinants of health.

Objective

This review aimed to characterize the state of the existing literature on the use of nonclinical health indicators in conjunction with clinical data sources.

Methods

We conducted a rapid review of articles and relevant agency publications published in English. Eligible studies described the effect of, the methods for, or the need for combining nonclinical data with clinical data and were published in the United States between January 2010 and April 2018. Additional reports were obtained by manual searching. Records were screened for inclusion in 2 rounds by 4 trained reviewers with interrater reliability checks. From each article, we abstracted the measures, data sources, and level of measurement (individual or aggregate) for each nonclinical determinant of health reported.

Results

A total of 178 articles were included in the review. The articles collectively reported on 744 different nonclinical determinants of health measures. Measures related to socioeconomic status and material conditions were most prevalent (included in 90% of articles), followed by the closely related domain of social circumstances (included in 25% of articles), reflecting the widespread availability and use of standard demographic measures such as household income, marital status, education, race, and ethnicity in public health surveillance. Measures related to health-related behaviors (eg, smoking, diet, tobacco, and substance abuse), the built environment (eg, transportation, sidewalks, and buildings), natural environment (eg, air quality and pollution), and health services and conditions (eg, provider of care supply, utilization, and disease prevalence) were less common, whereas measures related to public policies were rare. When combining nonclinical and clinical data, a majority of studies associated aggregate, area-level nonclinical measures with individual-level clinical data by matching geographical location.

Conclusions

A variety of nonclinical determinants of health measures have been widely but unevenly used in conjunction with clinical data to support population health research.

3-Bromopyruvate potentiates TRAIL-induced apoptosis in human colon cancer cells through a reactive oxygen species- and caspase-dependent mitochondrial pathway

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is a promising anticancer cytokine with minimal toxicity towards normal cells. Nevertheless, most primary cancers are often intrinsically TRAIL-resistant or can acquire resistance after TRAIL therapy. This study aimed to investigate the inhibitory effect of co-treatment of 3-bromopyruvate (3-BP) as a potent anticancer agent with TRAIL on colon cancer cells (HT-29). The results of present study indicated that combined treatment with 3-BP and TRAIL inhibited the proliferation of HT-29 cells to a greater extent (88.4%) compared with 3-BP (54%) or TRAIL (11%) treatment alone. In contrast, the combination of 3-BP and TRAIL had no significant inhibitory effect on the proliferation of normal cells (HEK-293) (8.4%). At a cellular mechanistic level, the present study showed that 3-BP sensitized human colon cancer cells to TRAIL-induced apoptosis via reactive oxygen species generation, upregulation of Bax, downregulation of Bcl-2 and survivin, release of cytochrome c into the cytosol, and activation of caspase-3. In normal cells, 3-BP, TRAIL, or combination of both had no significant effect on the reactive oxygen species levels, release of cytochrome c, and caspase-3 activity. Therefore, the combination of 3-BP and TRAIL can be a promising therapeutic strategy for treatment of colon cancer.

Roles of Cyclin A, Myc, Jun and Ppm1l in tumourigenic transformation of NIH3T3 cell

To analyse the mechanism of tumourigenic transformation of NIH3T3 cells at the transcriptional level, we used cancerogen 3-methylcholanthrene (3-MCA) and cancerogenic substance phorbol-12-myristate-13-acetate (PMA) to transform NIH3T3 cells and the assessment of transformation was performed using Giemsa staining and methylcellulose colony formation assay. Changes in gene expression profile were detected by Mouse Genome 430 2.0 microarray; and quantitative real-time polymerase chain reaction and Western blotting were used to verify the expression changes of mRNAs and proteins, respectively. With the aid of bioinformatics method, five signalling pathways were identified to participate in different stages of NIH3T3 cell transformation. Further, our study suggested that oncogenes Cyclin A, Myc, Jun and the tumour suppressor gene Ppm1l may play important roles in these pathways.

Disparities in minimally invasive surgery for colorectal cancer in Florida

BACKGROUND

The cost of minimally invasive surgery (MIS) raises potential for racial and social disparities. The aim of this study was to identify the racial, socioeconomic and geographic disparities associated with MIS for colorectal cancer (CRC) in Florida.

METHODS

Using the Florida Inpatient Discharge Dataset, we examined the clinical data of patients who underwent elective resections for CRC during 2013-2015. Multivariable analysis was performed to identify differences in gender, age, race, urbanization, region, insurance and clinical characteristics associated with the surgical approach.

RESULTS

Of the 10,224 patients identified, 5308 (52%) had open surgery and 4916 (48%) had MIS. Females (p = 0.012), Medicare-insured patients (p = 0.001) and residents of South Florida were more likely to undergo MIS. Patients with Medicaid (p = 0.008), metastasis (p < 0.001) or 3-5 comorbidities (p = 0.004) had reduced likelihood of MIS. Hispanic patients in Southwest Florida had reduced likelihood of receiving MIS than whites (p < 0.017). Patients who underwent MIS had significantly reduced LOS (p < 0.001).

CONCLUSIONS

Consistent with national studies, MIS for CRC in Florida is associated with insurance status and geographic location. There are patient-level regional differences for racial disparities in MIS for CRC in Florida.

Age-Specific Risk Factors for Advanced Stage Colorectal Cancer, 1981-2013

INTRODUCTION

Epidemiologic studies have identified an increase in colorectal cancer (CRC) among younger adults. By using a statewide population-based cancer registry, this study examines sociodemographic and clinical disparities in CRC and characterizes advanced stage CRC risk factors with specific attention to age-specific risk factors.

METHODS

Data from the Florida Cancer Data System from 1981 through 2013 were analyzed for adult CRC patients. Patients were divided into 2 age groups: younger than 50 years and 50 years or older. Stage of presentation was categorized as early (localized) or advanced (regional or distant). Multivariable logistic regression models adjusted for sociodemographic and clinical characteristics were fitted to identify risk factors for advanced stage CRC presentation. Adjusted odds ratios were calculated with 95% confidence intervals.

RESULTS

From 1981 through 2013, there were 182,095 Florida adults diagnosed with CRC. Those aged younger than 50 years were significantly more likely to have advanced stage CRC compared with those aged 50 or older. Among those younger than 50 years, current and former tobacco smokers and those of black or other race were significantly more likely to have advanced stage CRC. Among those aged 50 or older, Hispanics had significantly higher risk of advanced stage presentation compared with non-Hispanics, although this association was not significant in those younger than 50 years.

CONCLUSION

We identified significant age-specific risk factors for advanced stage CRC presentation. With CRC incidence on the rise among younger adults, it is important to identify and to target screening and interventions for groups at high risk for advanced stage CRC presentation.