Background and Aims: The incidence and mortality of colorectal cancer is persistently highest in Black/African-Americans in the United States. While access to care, barriers to screening, and poverty might explain these findings, there in increased interest in examining biological factors that impact the colonic environment. Our group is examining biologic factors that contribute to disparities in development of adenomas prospectively. In preparation for this and to characterize a potential patient population, we conducted a retrospective review of initial screening colonoscopies in a cohort of patients. Methods: A retrospective review was performed on initial average risk screening colonoscopies on patients (age 45 - 75 years) during 2012 at three institutions. Descriptive statistics and multivariable logistic regression models were used to examine the relationship between potential risk factors and the detection of adenomas. Results: Of the 2225 initial screening colonoscopies 1495 (67.2%) were performed on Black/African-Americans and 566 (25.4%) on Caucasians. Multivariable logistic regression revealed that older age, male sex, current smoking and teaching gastroenterologists were associated with higher detection of adenomas and these were less prevalent among Black/African- Americas except for age. Neither race, ethnicity, BMI, diabetes mellitus, HIV nor insurance w as associated with adenoma detection. Conclusion: In this sample, there was no association between race and adenoma detection. While this may be due to a lower prevalence of risk factors for adenomas in this sample, our findings were confounded by a lower detection rate by consultant gastroenterologists at one institution. The study allowed us to rectify the problem and characterize patients for future trials.
Colorectal Cancer (CRC) is the fourth most common cancer in the United States (US) and second most lethal [
Multiple studies have reported increased risk of colon cancer regardless of racial group to be associated with age, male sex, family history in a first degree relative, smoking, as well as diabetes mellitus and BMI which can be a reflection of diet and activity level [
The incidence and mortality of colon cancer remains significantly higher in Blacks/African-Americans than all other races and ethnicities in this US [
To test these hypotheses, we conducted a retrospective chart review of initial screening colonoscopies performed at three collaborating institutions: SUNY Downstate Medical Center (DMC), New York City Health and Hospitals/Kings County (Kings County), and Stony Brook University Hospital (SBUMC). DMC and SBUMC are funded by New York State while Kings County is supported by the New York Health and Hospital Corporation. DMC and Kings County are in central Brooklyn and SBUMC is in Long Island, New York. All three institutions educate residents and fellows and all three employ consultant gastroenterologists from time to time.
Collection of clinical data from initial screening colonoscopies performed in 2012
This study was approved by the Institutional Review Boards for all three institutions (IRB # 802718 for DMC and Kings County, approved 07/21/2017; IRB # 966231 for SBUMC, approved 03/21/2017). Patients who underwent screening colonoscopies between January 1 and December 31, 2012, were identified using the endoscopy reporting software at each of the three institutions.
Patients age < 45 y or >75 y, a history of previous colonoscopy, a history of inflammatory bowel diseases, known hereditary colorectal syndromes, detection of microscopic or macroscopic blood in stool and other alarm symptoms, detection of colonic masses or polyps on previous studies, were excluded from this analysis. We excluded colonoscopies that were incomplete (did not reach the cecum) and those associated with poor bowel preparation.
The clinical metadata was collected using the same data vocabulary at the three institutions and included: 1) age (y) at time of initial screening colonoscopy; 2) sex (male/female); 3) race (Black/Caucasian/Other); 4) ethnicity (Hispanic/non-Hispanic); 5) BMI (kg/m2); 6) diabetes mellitus (diagnosed, not diagnosed); 7) smoking (current/ not current); 8) HIV-1 (diagnosed/not diagnosed); 9) gastroenterologist (teaching versus consultant); and 10) insurance status (Commercial, Medicare, Medicaid, Self-pay). Patients who had both Commercial and Medicare insurance were classified in the Commercial category. Patients who had both Medicare and Medicaid insurance were classified in the Medicare category. Family history of colon cancer or a polyp in a first degree relative, was not included in the analysis since that data was unevenly collected.
2225 patients with colonoscopy screening were used in this analysis: DMC (N = 444, 20%), Kings County (N = 1134, 51%), SBUMC (N = 647, 29%). The outcomes of interest were: adenomas, advanced adenomas, and right colon adenomas.
Statistical analysis
Descriptive statistics and multivariable logistic regression models were used to examine the relationship between potential risk factors and the detection of three different types of adenomas (all adenomas, advanced adenomas, and right colon adenomas). Due to the high correlation between “race” and “institution”, three sets of multivariable logistic regression models were fitted for each clinical outcome: 1) both “race” and “institution” were used in the model; 2) only “race” was used in the model; and 3) only “institution” was used in the model. Since, in general, significant risk factors from 3 multivariable regression models were consistent, and based on c-index values, results from the models that contained both “race” and “institution” were reported here.
In each multivariable regression analysis, an OR > 1 indicates that one category has more risk of having adenoma detection than the reference category, and OR < 1 indicates that one category has less risk of having adenoma detection than the reference category. Generalized linear mixed models considering patients from the same institution as clusters were also considered. However, since there is no strong evidence that patients with same institution were highly correlated, results from logistic regression models were only reported here. Statistical analysis was performed using SAS 9.4 and significance level was set at 0.05 (SAS Institute, Inc., Cary, NC).
Variable | Missing | level | total | DMC (N = 444) | Kings county (N = 1134) | SBUMC (N = 647) | P-value1 |
---|---|---|---|---|---|---|---|
Adenoma | 0 | Yes | 494 (22.20%) | 132 (29.73%) | 194 (17.11%) | 168 (25.97%) | <0.0001 |
No | 1731 (77.80%) | 312 (70.27%) | 940 (82.89%) | 479 (74.03%) | |||
Advanced adenoma | 0 | Yes | 98 (4.40%) | 15 (3.38%) | 42 (3.70%) | 41 (6.34%) | 0.0168 |
No | 2127 (95.60%) | 429 (96.62%) | 1092 (96.30%) | 606 (93.66%) | |||
Right colon adenoma | 0 | Yes | 316 (14.20%) | 77 (17.34%) | 142 (12.52%) | 97 (14.99%) | 0.0378 |
No | 1909 (85.80%) | 367 (82.66%) | 992 (87.48%) | 550 (85.01%) | |||
Age (continuous) | 0 | 444 vs 1134 vs 647 | 57.00 ± 10.73 | 58.00 ± 12.00 | 57.63 ± 10.73 | 55.00 ± 10.00 | <0.0001 |
Age (categorical) | 0 | 45 - 54 | 879 (39.51%) | 144 (32.43%) | 438 (38.62%) | 297 (45.90%) | <0.0001 |
55 - 64 | 919 (41.30%) | 187 (42.12%) | 490 (43.21%) | 242 (37.40%) | |||
≥ 65 | 427 (19.19%) | 113 (25.45%) | 206 (18.17%) | 108 (16.69%) | |||
BMI (continuous) | 34 | 413 vs 1131 vs 647 | 28.27 ± 7.29 | 28.30 ± 7.80 | 28.60 ± 7.30 | 27.48 ± 6.44 | 0.0002 |
BMI (categorical) | 33 | Obese (BMI ≥ 30) | 829 (37.82%) | 166 (40.10%) | 460 (40.67%) | 203 (31.38%) | 0.0015 |
Overweight (BMI ≥ 25, <30) | 844 (38.50%) | 147 (35.51%) | 430 (38.02%) | 267 (41.27%) | |||
Underweight + Healthy (BMI < 25) | 519 (23.68%) | 101 (24.40%) | 241 (21.31%) | 177 (27.36%) | |||
Gender | 0 | Female | 1437 (64.58%) | 276 (62.16%) | 772 (68.08%) | 389 (60.12%) | 0.0016 |
Male | 788 (35.42%) | 168 (37.84%) | 362 (31.92%) | 258 (39.88%) | |||
Insurance | 0 | Private | 759 (34.11%) | 129 (29.05%) | 195 (17.20%) | 435 (67.23%) | <0.0001 |
Medicare | 236 (10.61%) | 95 (21.40%) | 57 (5.03%) | 84 (12.98%) | |||
Medicaid | 695 (31.24%) | 187 (42.12%) | 404 (35.63%) | 104 (16.07%) | |||
Self-Pay | 535 (24.04%) | 33 (7.43%) | 478 (42.15%) | 24 (3.71%) | |||
Race | 0 | African-American | 1117 (50.20%) | 175 (39.41%) | 900 (79.37%) | 42 (6.49%) | <0.0001 |
Afro-Caribbean | 378 (16.99%) | 216 (48.65%) | 160 (14.11%) | 2 (0.31%) | |||
American Indian or Alaskan Native | 2 (0.09%) | 0 (0.00%) | 1 (0.09%) | 1 (0.15%) | |||
Asian | 43 (1.93%) | 6 (1.35%) | 9 (0.79%) | 28 (4.33%) | |||
Other | 119 (5.35%) | 13 (2.93%) | 59 (5.20%) | 47 (7.26%) | |||
White | 566 (25.44%) | 34 (7.66%) | 5 (0.44%) | 527 (81.45%) | |||
Race combined | 0 | White | 566 (25.44%) | 34 (7.66%) | 5 (0.44%) | 527 (81.45%) | <0.0001 |
Black | 1495 (67.19%) | 391 (88.06%) | 1060 (93.47%) | 44 (6.80%) | |||
Other | 164 (7.37%) | 19 (4.28%) | 69 (6.08%) | 76 (11.75%) | |||
Ethnicity | 0 | Hispanic | 134 (6.02%) | 33 (7.43%) | 46 (4.06%) | 55 (8.50%) | 0.0003 |
Non-Hispanic | 2091 (93.98%) | 411 (92.57%) | 1088 (95.94%) | 592 (91.50%) | |||
Type of Attending | 0 | Consultant | 1058 (47.55%) | 25 (5.63%) | 976 (86.07%) | 57 (8.81%) | <0.0001 |
Teaching | 1167 (52.45%) | 419 (94.37%) | 158 (13.93%) | 590 (91.19%) |
Fellow | 0 | Yes | 247 (11.10%) | 6 (1.35%) | 132 (11.64%) | 109 (16.85%) | <0.0001 |
---|---|---|---|---|---|---|---|
No | 1978 (88.90%) | 438 (98.65%) | 1002 (88.36%) | 538 (83.15%) | |||
Tobacco use | 68 | Current | 202 (9.36%) | 53 (14.10%) | 66 (5.82%) | 83 (12.83%) | <0.0001 |
Not current | 1955 (90.64%) | 323 (85.90%) | 1068 (94.18%) | 564 (87.17%) | |||
Diabetes | 0 | Yes | 552 (24.81%) | 135 (30.41%) | 339 (29.89%) | 78 (12.06%) | <0.0001 |
No | 1673 (75.19%) | 309 (69.59%) | 795 (70.11%) | 569 (87.94%) | |||
HIV Status | 1 | Yes | 85 (3.82%) | 38 (8.56%) | 42 (3.70%) | 5 (0.77%) | <0.0001 |
No | 2139 (96.18%) | 406 (91.44%) | 1092 (96.30%) | 641 (99.23%) | |||
Insulin Use | 7 | Yes | 165 (7.44%) | 37 (8.45%) | 114 (10.05%) | 14 (2.17%) | <0.0001 |
No | 380 (17.13%) | 92 (21.00%) | 225 (19.84%) | 63 (9.75%) | |||
No diabetes | 1673 (75.43%) | 309 (70.55%) | 795 (70.11%) | 569 (88.08%) | |||
Metformin Use | 8 | Yes | 365 (16.46%) | 60 (13.70%) | 253 (22.33%) | 52 (8.05%) | <0.0001 |
No | 179 (8.07%) | 69 (15.75%) | 85 (7.50%) | 25 (3.87%) | |||
No diabetes | 1673 (75.46%) | 309 (70.55%) | 795 (70.17%) | 569 (88.08%) |
1For categorical variables, P-value was based on Chi-squared test with exact P-value from Monte Carlo simulation. For continuous variables, P-value was based on Wilcoxon rank sum test and median with IQR were reported. *Since 1 patient from DMC institution had BMI as “>30”, this patient was treated as having missing value when using BMI as continuous values.
Adenoma | ||||||
---|---|---|---|---|---|---|
Variable | Missing | Level | Total | Yes (N = 494, 22.2%) | No (N = 1731, 77.8%) | P-value1 |
Age (continuous) | 0 | 494 vs 1731 | 57.00 ± 10.73 | 58.76 ± 11.39 | 56.85 ± 10.84 | <0.0001 |
Age (categorical) | 0 | 45 - 54 | 879 (39.51%) | 159 (32.19%) | 720 (41.59%) | 0.0002 |
55 - 64 | 919 (41.30%) | 216 (43.72%) | 703 (40.61%) | |||
≥65 | 427 (19.19%) | 119 (24.09%) | 308 (17.79%) | |||
BMI (continuous) | 34 | 481 vs 1710 | 28.27 ± 7.29 | 28.00 ± 6.50 | 28.30 ± 7.35 | 0.1718 |
BMI (categorical) | 33 | Obese (BMI ≥ 30) | 829 (37.82%) | 168 (34.85%) | 661 (38.65%) | 0.2609 |
Overweight (BMI ≥ 25, <30) | 844 (38.50%) | 199 (41.29%) | 645 (37.72%) | |||
Underweight + Healthy (BMI < 25) | 519 (23.68%) | 115 (23.86%) | 404 (23.63%) | |||
Gender | 0 | Female | 1437 (64.58%) | 275 (55.67%) | 1162 (67.13%) | <0.0001 |
Male | 788 (35.42%) | 219 (44.33%) | 569 (32.87%) | |||
Insurance | 0 | Private | 759 (34.11%) | 179 (36.23%) | 580 (33.51%) | <0.0001 |
Medicare | 236 (10.61%) | 79 (15.99%) | 157 (9.07%) | |||
Medicaid | 695 (31.24%) | 142 (28.74%) | 553 (31.95%) | |||
Self-Pay | 535 (24.04%) | 94 (19.03%) | 441 (25.48%) |
Institution | 0 | DMC | 444 (19.96%) | 132 (26.72%) | 312 (18.02%) | <0.0001 |
---|---|---|---|---|---|---|
Kings county | 1134 (50.97%) | 194 (39.27%) | 940 (54.30%) | |||
SBUMC | 647 (29.08%) | 168 (34.01%) | 479 (27.67%) | |||
Race | 0 | African-American | 1117 (50.20%) | 207 (41.90%) | 910 (52.57%) | 0.0005 |
Afro-Caribbean | 378 (16.99%) | 90 (18.22%) | 288 (16.64%) | |||
American Indian or Alaskan Native | 2 (0.09%) | 0 (0.00%) | 2 (0.12%) | |||
Asian | 43 (1.93%) | 10 (2.02%) | 33 (1.91%) | |||
Other | 119 (5.35%) | 37 (7.49%) | 82 (4.74%) | |||
White | 566 (25.44%) | 150 (30.36%) | 416 (24.03%) | |||
Race combined | 0 | White | 566 (25.44%) | 150 (30.36%) | 416 (24.03%) | 0.0006 |
Black | 1495 (67.19%) | 297 (60.12%) | 1198 (69.21%) | |||
Other | 164 (7.37%) | 47 (9.51%) | 117 (6.76%) | |||
Ethnicity | 0 | Hispanic | 134 (6.02%) | 35 (7.09%) | 99 (5.72%) | 0.2604 |
Non-Hispanic | 2091 (93.98%) | 459 (92.91%) | 1632 (94.28%) | |||
Type of Attending | 0 | Consultant | 1058 (47.55%) | 181 (36.64%) | 877 (50.66%) | <0.0001 |
Teaching | 1167 (52.45%) | 313 (63.36%) | 854 (49.34%) | |||
Fellow | 0 | Yes | 247 (11.10%) | 60 (12.15%) | 187 (10.80%) | 0.4021 |
No | 1978 (88.90%) | 434 (87.85%) | 1544 (89.20%) | |||
Tobacco use | 68 | Current | 202 (9.36%) | 61 (12.79%) | 141 (8.39%) | 0.0036 |
Not current | 1955 (90.64%) | 416 (87.21%) | 1539 (91.61%) | |||
Diabetes | 0 | Yes | 552 (24.81%) | 141 (28.54%) | 411 (23.74%) | 0.0294 |
No | 1673 (75.19%) | 353 (71.46%) | 1320 (76.26%) | |||
HIV Status | 1 | Yes | 85 (3.82%) | 11 (2.23%) | 74 (4.27%) | 0.041 |
No | 2139 (96.18%) | 482 (97.77%) | 1657 (95.73%) | |||
Advanced adenoma | ||||||
Variable | Missing | Level | Total | Yes (N=98, 4.4%) | No (N=2127, 95.6%) | P-value1 |
Age (continuous) | 0 | 98 vs 2127 | 57.00 ± 10.73 | 57.46 ± 10.26 | 57.00 ± 10.78 | 0.4729 |
Age (categorical) | 0 | 45 - 54 | 879 (39.51%) | 33 (33.67%) | 846 (39.77%) | 0.4746 |
55 - 64 | 919 (41.30%) | 45 (45.92%) | 874 (41.09%) | |||
≥65 | 427 (19.19%) | 20 (20.41%) | 407 (19.13%) | |||
BMI (continuous) | 34 | 98 vs 2093 | 28.27 ± 7.29 | 28.45 ± 7.30 | 28.20 ± 7.20 | 0.7217 |
BMI (categorical) | 33 | Obese (BMI ≥ 30) | 829 (37.82%) | 34 (34.69%) | 795 (37.97%) | 0.5332 |
Overweight (BMI ≥ 25, <30) | 844 (38.50%) | 43 (43.88%) | 801 (38.25%) | |||
Underweight + Healthy (BMI < 25) | 519 (23.68%) | 21 (21.43%) | 498 (23.78%) |
Gender | 0 | Female | 1437 (64.58%) | 55 (56.12%) | 1382 (64.97%) | 0.0732 |
---|---|---|---|---|---|---|
Male | 788 (35.42%) | 43 (43.88%) | 745 (35.03%) | |||
Insurance | 0 | Private | 759 (34.11%) | 31 (31.63%) | 728 (34.23%) | 0.0691 |
Medicare | 236 (10.61%) | 18 (18.37%) | 218 (10.25%) | |||
Medicaid | 695 (31.24%) | 25 (25.51%) | 670 (31.50%) | |||
Self-Pay | 535 (24.04%) | 24 (24.49%) | 511 (24.02%) | |||
Institution | 0 | DMC | 444 (19.96%) | 15 (15.31%) | 429 (20.17%) | 0.0168 |
Kings county | 1134 (50.97%) | 42 (42.86%) | 1092 (51.34%) | |||
SBUMC | 647 (29.08%) | 41 (41.84%) | 606 (28.49%) | |||
Race | 0 | African-American | 1117 (50.20%) | 41 (41.84%) | 1076 (50.59%) | 0.35 |
Afro-Caribbean | 378 (16.99%) | 17 (17.35%) | 361 (16.97%) | |||
American Indian or Alaskan Native | 2 (0.09%) | 0 (0.00%) | 2 (0.09%) | |||
Asian | 43 (1.93%) | 1 (1.02%) | 42 (1.97%) | |||
Other | 119 (5.35%) | 8 (8.16%) | 111 (5.22%) | |||
White | 566 (25.44%) | 31 (31.63%) | 535 (25.15%) | |||
Race combined | 0 | White | 566 (25.44%) | 31 (31.63%) | 535 (25.15%) | 0.2252 |
Black | 1495 (67.19%) | 58 (59.18%) | 1437 (67.56%) | |||
Other | 164 (7.37%) | 9 (9.18%) | 155 (7.29%) | |||
Ethnicity | 0 | Hispanic | 134 (6.02%) | 5 (5.10%) | 129 (6.06%) | 0.6953 |
Non-Hispanic | 2091 (93.98%) | 93 (94.90%) | 1998 (93.94%) | |||
Type of Attending | 0 | Consultant | 1058 (47.55%) | 37 (37.76%) | 1021 (48.00%) | 0.047 |
Teaching | 1167 (52.45%) | 61 (62.24%) | 1106 (52.00%) | |||
Fellow | 0 | Yes | 247 (11.10%) | 19 (19.39%) | 228 (10.72%) | 0.0076 |
No | 1978 (88.90%) | 79 (80.61%) | 1899 (89.28%) | |||
Tobacco use | 68 | Current | 202 (9.36%) | 18 (18.37%) | 184 (8.94%) | 0.0034 |
Not current | 1955 (90.64%) | 80 (81.63%) | 1875 (91.06%) | |||
Diabetes | 0 | Yes | 552 (24.81%) | 29 (29.59%) | 523 (24.59%) | 0.2622 |
No | 1673 (75.19%) | 69 (70.41%) | 1604 (75.41%) | |||
HIV Status | 1 | Yes | 85 (3.82%) | 1 (1.02%) | 84 (3.95%) | 0.1801 |
No | 2139 (96.18%) | 97 (98.98%) | 2042 (96.05%) | |||
Right colon adenoma | ||||||
Variable | Missing | Level | Total | Yes (N = 316, 14.2%) | No (N = 1909, 85.8%) | P-value1 |
Age (continuous) | 0 | 316 vs 1909 | 57.00 ± 10.73 | 58.96 ± 10.49 | 57.00 ± 10.98 | <0.0001 |
Age (categorical) | 0 | 45 - 54 | 879 (39.51%) | 98 (31.01%) | 781 (40.91%) | 0.002 |
55 - 64 | 919 (41.30%) | 142 (44.94%) | 777 (40.70%) | |||
≥65 | 427 (19.19%) | 76 (24.05%) | 351 (18.39%) |
BMI (continuous) | 34 | 305 vs 1886 | 28.27 ± 7.29 | 28.00 ± 6.70 | 28.30 ± 7.20 | 0.2358 |
---|---|---|---|---|---|---|
BMI (categorical) | 33 | Obese (BMI ≥ 30) | 829 (37.82%) | 106 (34.64%) | 723 (38.34%) | 0.4615 |
Overweight (BMI ≥ 25, <30) | 844 (38.50%) | 123 (40.20%) | 721 (38.23%) | |||
Underweight + Healthy (BMI < 25) | 519 (23.68%) | 77 (25.16%) | 442 (23.44%) | |||
Gender | 0 | Female | 1437 (64.58%) | 181 (57.28%) | 1256 (65.79%) | 0.0034 |
Male | 788 (35.42%) | 135 (42.72%) | 653 (34.21%) | |||
Insurance | 0 | Private | 759 (34.11%) | 110 (34.81%) | 649 (34.00%) | 0.0004 |
Medicare | 236 (10.61%) | 54 (17.09%) | 182 (9.53%) | |||
Medicaid | 695 (31.24%) | 89 (28.16%) | 606 (31.74%) | |||
Self-Pay | 535 (24.04%) | 63 (19.94%) | 472 (24.72%) | |||
Institution | 0 | DMC | 444 (19.96%) | 77 (24.37%) | 367 (19.22%) | 0.0378 |
Kings county | 1134 (50.97%) | 142 (44.94%) | 992 (51.96%) | |||
SBUMC | 647 (29.08%) | 97 (30.70%) | 550 (28.81%) | |||
Race | 0 | African-American | 1117 (50.20%) | 146 (46.20%) | 971 (50.86%) | 0.2208 |
Afro-Caribbean | 378 (16.99%) | 52 (16.46%) | 326 (17.08%) | |||
American Indian or Alaskan Native | 2 (0.09%) | 0 (0.00%) | 2 (0.10%) | |||
Asian | 43 (1.93%) | 7 (2.22%) | 36 (1.89%) | |||
Other | 119 (5.35%) | 25 (7.91%) | 94 (4.92%) | |||
White | 566 (25.44%) | 86 (27.22%) | 480 (25.14%) | |||
Race combined | 0 | White | 566 (25.44%) | 86 (27.22%) | 480 (25.14%) | 0.0679 |
Black | 1495 (67.19%) | 198 (62.66%) | 1297 (67.94%) | |||
Other | 164 (7.37%) | 32 (10.13%) | 132 (6.91%) | |||
Ethnicity | 0 | Hispanic | 134 (6.02%) | 23 (7.28%) | 111 (5.81%) | 0.311 |
Non-Hispanic | 2091 (93.98%) | 293 (92.72%) | 1798 (94.19%) | |||
Type of Attending | 0 | Consultant | 1058 (47.55%) | 126 (39.87%) | 932 (48.82%) | 0.0032 |
Teaching | 1167 (52.45%) | 190 (60.13%) | 977 (51.18%) | |||
Fellow | 0 | Yes | 247 (11.10%) | 36 (11.39%) | 211 (11.05%) | 0.8588 |
No | 1978 (88.90%) | 280 (88.61%) | 1698 (88.95%) | |||
Tobacco use | 68 | Current | 202 (9.36%) | 35 (11.40%) | 167 (9.03%) | 0.1862 |
Not current | 1955 (90.64%) | 272 (88.60%) | 1683 (90.97%) | |||
Diabetes | 0 | Yes | 552 (24.81%) | 91 (28.80%) | 461 (24.15%) | 0.0764 |
No | 1673 (75.19%) | 225 (71.20%) | 1448 (75.85%) | |||
HIV Status | 1 | Yes | 85 (3.82%) | 6 (1.90%) | 79 (4.14%) | 0.056 |
No | 2139 (96.18%) | 309 (98.10%) | 1830 (95.86%) |
1For categorical variables, P-value was based on Chi-squared test with exact P-value from Monte Carlo simulation. For continuous variables, P-value was based on Wilcoxon rank sum test and median with IQR were reported. *Since 1 patient from DMC institution had BMI as “>30”, this patient was treated as having missing value when using BMI as continuous values.
Variable | Levels | Odds Ratio (95% CI) | P-value2 |
---|---|---|---|
Age | Every 1 year increase in Age | 1.027 (1.01 - 1.04) | 0.0009 |
BMI | Every 1 unit increase in BMI | 0.987 (0.97 - 1.01) | 0.1658 |
Gender | Female vs Male | 0.626 (0.5 - 0.78) | <0.0001 |
Insurance | Private vs Medicare | 0.767 (0.53 - 1.1) | 0.404 |
Private vs Medicaid | 1.053 (0.79 - 1.4) | ||
Private vs Self-Pay | 1.003 (0.71 - 1.41) | ||
Medicare vs Medicaid | 1.373 (0.94 - 1.99) | ||
Medicare vs Self-Pay | 1.308 (0.86 - 2) | ||
Medicaid vs Self-Pay | 0.953 (0.69 - 1.31) | ||
Institution | DMC vs Kings county | 1.515 (0.94 - 2.43) | 0.0694 |
DMC vs SBUMC | 1.605 (0.99 - 2.59) | ||
Kings county vs SBUMC | 1.059 (0.59 - 1.89) | ||
Race combined | White vs Black | 1.426 (0.89 - 2.29) | 0.1116 |
White vs Other | 0.849 (0.53 - 1.37) | ||
Black vs Other | 0.596 (0.36 - 0.98) | ||
Ethnicity | Hispanic vs Non-Hispanic | 0.986 (0.6 - 1.62) | 0.957 |
Type of attending | Consultant vs Teaching | 0.741 (0.49 - 1.12) | 0.1543 |
Fellow | Yes vs No | 1.176 (0.8 - 1.74) | 0.4155 |
Tobacco use | Current vs Not current | 1.499 (1.07 - 2.11) | 0.0195 |
Diabetes | Yes vs No | 1.265 (0.98 - 1.63) | 0.066 |
HIV status | Yes vs No | 0.473 (0.24 - 0.95) | 0.0348 |
2P-value was based on type3 analysis from multivariable logistic regression model.
Variable | Levels | Odds Ratio (95% CI) | P-value2 |
---|---|---|---|
Insurance | Private vs Medicare | 0.448 (0.24 - 0.82) | 0.0245 |
Private vs Medicaid | 1.137 (0.66 - 1.95) | ||
Private vs Self-Pay | 0.875 (0.51 - 1.51) | ||
Medicare vs Medicaid | 2.54 (1.35 - 4.78) | ||
Medicare vs Self-Pay | 1.953 (1.03 - 3.7) | ||
Medicaid vs Self-Pay | 0.769 (0.43 - 1.37) | ||
Fellow | Yes vs No | 1.912 (1.13 - 3.24) | 0.0158 |
Tobacco use | Current vs Not current | 2.362 (1.37 - 4.06) | 0.0019 |
2P-value was based on type3 analysis from multivariable logistic regression model.
Variable | Levels | Odds Ratio (95% CI) | P-value2 |
---|---|---|---|
Age | Every 1 year increase in Age | 1.026 (1.01 - 1.05) | 0.0067 |
BMI | Every 1 unit increase in BMI | 0.986 (0.96 - 1.01) | 0.2226 |
Gender | Female vs Male | 0.694 (0.54 - 0.9) | 0.0049 |
Insurance | Private vs Medicare | 0.689 (0.46 - 1.04) | 0.0911 |
Private vs Medicaid | 1.182 (0.84 - 1.66) | ||
Private vs Self-Pay | 1.154 (0.78 - 1.72) | ||
Medicare vs Medicaid | 1.714 (1.12 - 2.63) | ||
Medicare vs Self-Pay | 1.674 (1.03 - 2.71) | ||
Medicaid vs Self-Pay | 0.977 (0.68 - 1.41) | ||
Institution | DMC vs Kings county | 0.794 (0.45 - 1.41) | 0.1979 |
DMC vs SBUMC | 1.482 (0.84 - 2.62) | ||
Kings county vs SBUMC | 1.867 (0.93 - 3.74) | ||
Race combined | White vs Black | 1.337 (0.76 - 2.35) | 0.1355 |
White vs Other | 0.751 (0.43 - 1.32) | ||
Black vs Other | 0.561 (0.32 - 0.99) | ||
Ethnicity | Hispanic vs Non-Hispanic | 0.978 (0.55 - 1.75) | 0.9402 |
Type of attending | Consultant vs Teaching | 0.577 (0.35 - 0.95) | 0.0322 |
Fellow | Yes vs No | 0.89 (0.55 - 1.44) | 0.6373 |
Tobacco use | Current vs Not current | 1.302 (0.86 - 1.96) | 0.2075 |
Diabetes | Yes vs No | 1.143 (0.85 - 1.53) | 0.3706 |
HIV status | Yes vs No | 0.392 (0.15 - 0.99) | 0.0486 |
2P-value was based on type3 analysis from multivariable logistic regression model.
Outcome | variable | Levels | Both race and institution | Only race | Only institution | |||
---|---|---|---|---|---|---|---|---|
Odds Ratio (95% CI) | P-value2 | Odds Ratio (95% CI) | P-value2 | Odds Ratio (95% CI) | P-value2 | |||
Adenoma | Age | Every 1 year increase in Age | 1.027 (1.01 - 1.04) | 0.0009 | 1.028 (1.01 - 1.04) | 0.0006 | 1.027 (1.01 - 1.04) | 0.001 |
BMI | Every 1 unit increase in BMI | 0.987 (0.97 - 1.01) | 0.1658 | 0.986 (0.97 - 1) | 0.1483 | 0.985 (0.97 - 1) | 0.1247 | |
Insurance | Private vs Medicare | 0.767 (0.53 - 1.1) | 0.404 | 0.754 (0.53 - 1.08) | 0.3508 | 0.778 (0.54 - 1.12) | 0.4401 | |
Private vs Medicaid | 1.053 (0.79 - 1.4) | 1.04 (0.79 - 1.38) | 1.055 (0.79 - 1.41) | |||||
Private vs Self-Pay | 1.003 (0.71 - 1.41) | 1.047 (0.75 - 1.46) | 1.026 (0.73 - 1.44) | |||||
Medicare vs Medicaid | 1.373 (0.94 - 1.99) | 1.379 (0.95 - 2) | 1.355 (0.93 - 1.97) | |||||
Medicare vs Self-Pay | 1.308 (0.86 - 2) | 1.389 (0.92 - 2.1) | 1.318 (0.86 - 2.01) | |||||
Medicaid vs Self-Pay | 0.953 (0.69 - 1.31) | 1.007 (0.74 - 1.37) | 0.972 (0.71 - 1.33) | |||||
Institution | DMC vs Kings county | 1.515 (0.94 - 2.43) | 0.0694 | . | 1.521 (0.95 - 2.43) | 0.2029 | ||
DMC vs SBUMC | 1.605 (0.99 - 2.59) | 1.2 (0.87 - 1.65) | ||||||
Kings county vs SBUMC | 1.059 (0.59 - 1.89) | 0.789 (0.51 - 1.21) | ||||||
Gender | Female vs Male | 0.626 (0.5 - 0.78) | <0.0001 | 0.615 (0.5 - 0.76) | <0.0001 | 0.615 (0.5 - 0.76) | <0.0001 | |
Race combined | White vs Black | 1.426 (0.89 - 2.29) | 0.1116 | 1.094 (0.82 - 1.47) | 0.3334 | |||
White vs Other | 0.849 (0.53 - 1.37) | 0.781 (0.49 - 1.24) | ||||||
Black vs Other | 0.596 (0.36 - 0.98) | 0.714 (0.46 - 1.12) | ||||||
Ethnicity | Hispanic vs Non-Hispanic | 0.986 (0.6 - 1.62) | 0.957 | 1.062 (0.65 - 1.74) | 0.812 | 1.276 (0.84 - 1.94) | 0.256 | |
Type of attending | Consultant vs Teaching | 0.741 (0.49 - 1.12) | 0.1543 | 0.59 (0.45 - 0.77) | <0.0001 | 0.746 (0.49 - 1.13) | 0.1631 | |
Fellow | Yes vs No | 1.176 (0.8 - 1.74) | 0.4155 | 1.001 (0.71 - 1.41) | 0.9973 | 1.184 (0.8 - 1.75) | 0.3954 | |
Tobacco use | Current vs Not current | 1.499 (1.07 - 2.11) | 0.0195 | 1.522 (1.09 - 2.13) | 0.0147 | 1.485 (1.06 - 2.08) | 0.0225 | |
Diabetes | Yes vs No | 1.265 (0.98 - 1.63) | 0.066 | 1.267 (0.99 - 1.63) | 0.0644 | 1.254 (0.98 - 1.61) | 0.0761 | |
HIV status | Yes vs No | 0.473 (0.24 - 0.95) | 0.0348 | 0.505 (0.25 - 1.01) | 0.0523 | 0.466 (0.23 - 0.93) | 0.031 |
Advanced adenoma *Forward selection was further considered due to the limited event size | Insurance | Private vs Medicare | 0.448 (0.24 - 0.82) | 0.0245 | 0.448 (0.24 - 0.82) | 0.0245 | 0.448 (0.24 - 0.82) | 0.0245 |
---|---|---|---|---|---|---|---|---|
Private vs Medicaid | 1.137 (0.66 - 1.95) | 1.137 (0.66 - 1.95) | 1.137 (0.66 - 1.95) | |||||
Private vs Self-Pay | 0.875 (0.51 - 1.51) | 0.875 (0.51 - 1.51) | 0.875 (0.51 - 1.51) | |||||
Medicare vs Medicaid | 2.54 (1.35 - 4.78) | 2.54 (1.35 - 4.78) | 2.54 (1.35 - 4.78) | |||||
Medicare vs Self-Pay | 1.953 (1.03 - 3.7) | 1.953 (1.03 - 3.7) | 1.953 (1.03 - 3.7) | |||||
Medicaid vs Self-Pay | 0.769 (0.43 - 1.37) | 0.769 (0.43 - 1.37) | 0.769 (0.43 - 1.37) | |||||
Fellow | Yes vs No | 1.912 (1.13 - 3.24) | 0.0158 | 1.912 (1.13 - 3.24) | 0.0158 | 1.912 (1.13 - 3.24) | 0.0158 | |
Tobacco use | Current vs Not current | 2.362 (1.37 - 4.06) | 0.0019 | 2.362 (1.37 - 4.06) | 0.0019 | 2.362 (1.37 - 4.06) | 0.0019 | |
Right colon adenoma | Age | Every 1 year increase in Age | 1.026 (1.01 - 1.05) | 0.0067 | 1.027 (1.01 - 1.05) | 0.005 | 1.026 (1.01 - 1.04) | 0.0077 |
BMI | Every 1 unit increase in BMI | 0.986 (0.96 - 1.01) | 0.2226 | 0.986 (0.96 - 1.01) | 0.2192 | 0.985 (0.96 - 1.01) | 0.1789 | |
Insurance | Private vs Medicare | 0.689 (0.46 - 1.04) | 0.0911 | 0.676 (0.45 - 1.02) | 0.1334 | 0.698 (0.46 - 1.05) | 0.0994 | |
Private vs Medicaid | 1.182 (0.84 - 1.66) | 1.105 (0.79 - 1.54) | 1.179 (0.84 - 1.66) | |||||
Private vs Self-Pay | 1.154 (0.78 - 1.72) | 1.074 (0.73 - 1.58) | 1.174 (0.79 - 1.74) | |||||
Medicare vs Medicaid | 1.714 (1.12 - 2.63) | 1.635 (1.07 - 2.49) | 1.689 (1.1 - 2.58) | |||||
Medicare vs Self-Pay | 1.674 (1.03 - 2.71) | 1.588 (0.99 - 2.54) | 1.68 (1.04 - 2.71) | |||||
Medicaid vs Self-Pay | 0.977 (0.68 - 1.41) | 0.971 (0.68 - 1.4) | 0.995 (0.69 - 1.44) | |||||
Institution | DMC vs Kings county | 0.794 (0.45 - 1.41) | 0.1979 | 0.791 (0.45 - 1.4) | 0.3305 | |||
DMC vs SBUMC | 1.482 (0.84 - 2.62) | 1.156 (0.79 - 1.69) | ||||||
Kings county vs SBUMC | 1.867 (0.93 - 3.74) | 1.461 (0.87 - 2.46) | ||||||
Gender | Female vs Male | 0.694 (0.54 - 0.9) | 0.0049 | 0.69 (0.54 - 0.89) | 0.0043 | 0.681 (0.53 - 0.88) | 0.003 | |
Race combined | White vs Black | 1.337 (0.76 - 2.35) | 0.1355 | 0.917 (0.65 - 1.3) | 0.2423 | |||
White vs Other | 0.751 (0.43 - 1.32) | 0.636 (0.37 - 1.08) | ||||||
Black vs Other | 0.561 (0.32 - 0.99) | 0.694 (0.42 - 1.16) |
Ethnicity | Hispanic vs Non-Hispanic | 0.978 (0.55 - 1.75) | 0.9402 | 1.043 (0.59 - 1.85) | 0.8865 | 1.328 (0.82 - 2.16) | 0.2545 | |
---|---|---|---|---|---|---|---|---|
Type of attending | Consultant vs Teaching | 0.577 (0.35 - 0.95) | 0.0322 | 0.718 (0.53 - 0.98) | 0.0354 | 0.58 (0.35 - 0.96) | 0.0331 | |
Fellow | Yes vs No | 0.89 (0.55 - 1.44) | 0.6373 | 0.996 (0.66 - 1.5) | 0.9851 | 0.895 (0.55 - 1.45) | 0.6509 | |
Tobacco use | Current vs Not current | 1.302 (0.86 - 1.96) | 0.2075 | 1.266 (0.84 - 1.9) | 0.2578 | 1.292 (0.86 - 1.95) | 0.2206 | |
Diabetes | Yes vs No | 1.143 (0.85 - 1.53) | 0.3706 | 1.155 (0.86 - 1.55) | 0.3326 | 1.138 (0.85 - 1.52) | 0.3861 | |
HIV status | Yes vs No | 0.392 (0.15 - 0.99) | 0.0486 | 0.402 (0.16 - 1.02) | 0.0544 | 0.384 (0.15 - 0.97) | 0.0437 |
2P-value was based on type3 analysis from multivariable logistic regression model.
In this study our hypothesis that older age, male sex and current smoking were associated with a higher risk of detecting anadenoma was confirmed. These findings concur with those observed in a large study conducted by Kaiser Permanente and a meta-analysis of 18 studies examining risk factors for colon polyps [
Given that Black/African-Americans have a higher incidence of colon cancer, our pretest hypothesis was that Black/African-American race would be associated with a higher risk of detecting adenomas. However, in the univariate analysis, Caucasian race was associated with a higher risk and in the multivariable analysis race was not significantly associated with the risk of detecting anadenoma. A similar finding was noted in a smaller study among uninsured patients in New York [
Blacks/African-Americans receive screening at an older age which would confer a higher risk of adenomas but they had lower rates of the other risk factors such as male sex and current smoking. Additionally, this Black/African-American population may consist of subgroups that inherently have a lower risk for adenomas. Approximately half of the Black/African American patients seen at DMC and 40% of those at Kings County were documented as Afro Caribbean [
Another factor that likely contributed to the lack of association between race and adenomas is that the analysis may have been confounded by significant differences in the ADR of the gastroenterologists performing the procedures. A significantly higher proportion of colonoscopies among Black/African-American patients was performed by non-teaching or consultant gastroenterologists who had a significantly lower ADR at one of the three institutions. A recent study on interval colon cancer in Medicare enrollees noted that a higher proportion of black persons (52.8%) than white persons (46.2%) received colonoscopies from physicians with a lower Polyp Detection Rate [
A recent joint task force of the American College of Gastroenterology and the American Society of Gastrointestinal Endoscopy recommended ADR benchmarks of 25% for all patients and sex-specific rates of 30% for men and 20% for women [
Various colonoscopy screening programs have been implemented to improve access of uninsured and minority patients to screening colonoscopies [
The lack of any association with Black/African-American race and proximal adenoma is contrary to the observed distribution of right sided colon cancers in this population [
There have been conflicting observations of the prevalence of advanced adenomas in Black/African-American patients [
The American Cancer Society updated their CRC screening recommendations in May 2018 to initiate screening for all patients at age 45 years [
Although it is hypothesized that HIV infection increases the risk of Non-AIDS defining malignancies [
One of the major strengths of this study is the sample size and the representation of Black/African-Americans in the sample which allowed for comparisons of multiple variables with the Caucasian population. Additionally, the exclusion criteria ensured that only patients with average risk screening colonoscopies were included. The exclusion criteria also removed other determinants of ADR as incomplete studies and those with inadequate prep.
A major limitation of our study is the variation in ADR due to the type of gastroenterologist during 2012 which would have impacted the effect of other variables on detection of adenomas. Additionally, there are recent observations that some proximal serrated adenomas may have been misclassified as hyperplastic polyps and this is variable amongst pathologists [
In this study male sex, older age, current smoking and diabetes were associated with increased prevalence of adenoma. This finding may have been influenced by disparities in the ADR of gastroenterologists performing screening in the Black/African American populations. However, initiatives to improve quality have been implemented across all the institutions. Now that the effect of operator dependence has been greatly reduced, we plan to resume collection of data for this study beginning with 2019 to better define the populations at higher risk of adenoma. Further studies delineating the biologic factors including the microbiome affecting adenomas should also be conducted. The hope is that early preventive interventions to reduce the prevalence of these risk factors and treatment options targeting them may further reduce colon cancer incidence and mortality in this population.
We wish to thank all of the patients who contributed to this study and will continue to contribute to further studies. We thank Dr Moro Salifu for facilitating the collaboration between Stony Brook University and SUNY Downstate Medical Center. We also thank Jennifer Caceres, MD, Karthik Raghunathan, MD, Kirolos Iskander, MD, Michael Mann, Khalid Awwal for their assistance with data collection. We also acknowledge the biostatistical consultation and biostatistical support provided by the Biostatistical Consulting Core at School of Medicine, Stony Brook University. We would also like to thank those at NYC HHC Corp who reviewed and made constructive comments: Machelle Allen, MD, Steven Pulitzer, MD and Wendy Wilcox, MD.
Study concept and design: Joshua Miller, Ellen Li, Yakira David, Lorenzo Ottaviano. Data collection: Yakira David, Ellen Li, Lorenzo Ottaviano, Michelle Likhtshteyn, Sadat Iqbal, Samir Kumar, Brandon Lung, Helen Lyo, Jesse T. Frye, Ayanna E. Lewis. Analysis and Interpretation of Data: Ellen Li, Jihye Park, Jie Yang, Yakira David, Joshua Miller, Lorenzo Ottaviano,. Drafting of the Manuscript: Ellen Li, Yakira David, Michele Follen, Evan Grossman. Critical Review for Important Intellectual Content: Joshua Miller, Lorenzo Ottaviano, ShivakuarVignesh, Evan Grossman, Laura Martello, Ayanna E. Lewis, Michele Follen. Study Supervision: Laura Martello, Joshua Miller, Ellen Li, ShivakumarVignesh, Evan Grossman.
NCI P20 CA192994 (E.L.), Simons Foundation (E.L.), Stony Brook FUSION Seed Grant Award (J.D.M.). The work conducted is independent of the funding source.
Evan Grossman MD.
The authors declare no conflict of interest.
David, Y., Ottaviano, L., Park, J., Iqbal, S., Likhtshteyn, M., Kumar, S., Lyo, H., Lewism A.E., Lung, B.E., Frye, J.T., Huang, L., Li, E., Yang, J., Martello, L., Vignesh, S., Miller, J.D., Follen, M. and Grossman, E.B. (2019) Confounders in Adenoma Detection at Initial Screening Colonoscopy: A Factor in the Assessment of Racial Disparities as a Risk for Colon Cancer. Journal of Cancer Therapy, 10, 269-289. https://doi.org/10.4236/jct.2019.104022