Abstract
Purpose
Radiation therapy and surgery are fundamental site-directed therapies for nonmetastatic rectal cancer. To understand the relationship between rurality and access to specialized care, we characterized the association of rural patient residence with receipt of surgery and radiation therapy among Medicare beneficiaries with rectal cancer.
Methods and Materials
We identified fee-for-service Medicare beneficiaries aged 65 years or older diagnosed with nonmetastatic rectal cancer from 2016 to 2018. Beneficiary place of residence was assigned to one of 3 geographic categories (metropolitan, micropolitan, or small town/rural) based on census tract and corresponding rural urban commuting area codes. Multivariable regression models were used to determine associations between levels of rurality and receipt of both radiation and proctectomy within 180 days of diagnosis. In addition, we explored associations between patient rurality and characteristics of surgery and radiation such as minimally invasive surgery (MIS) or intensity modulated radiation therapy (IMRT).
Results
Among 13,454 Medicare beneficiaries with nonmetastatic rectal cancer, 3926 (29.2%) underwent proctectomy within 180 days of being diagnosed with rectal cancer, and 1792 (13.3%) received both radiation and proctectomy. Small town/rural residence was associated with an increased likelihood of receiving both radiation and proctectomy within 180 days of diagnosis (adjusted subhazard ratio, 1.15; 95% CI, 1.02-1.30). Furthermore, small town/rural radiation patients were significantly less likely to receive IMRT (adjusted odds ratio, 0.62; 95% CI, 0.48-0.80) or MIS (adjusted odds ratio, 0.80; 95% CI, 0.66-0.97) than metropolitan patients.
Conclusions
Although small town/rural Medicare beneficiaries were overall more likely to receive both radiation and proctectomy for their rectal cancer, they were less likely to receive preoperative IMRT or MIS as part of their treatment regimen. Together, these findings clarify that among Medicare beneficiaries, there appeared to be a similar utilization of radiation resources and time to radiation treatment regardless of rural/urban status.
Introduction
An estimated 45,230 new cases of rectal cancer were diagnosed in the United States in 2021, approximately two-thirds of which presented with nonmetastatic disease.1 For such patients, primary curative therapy requires total surgical excision of the mesorectum and its contents. Even with complete surgery, patients with stage II/III rectal cancer treated by surgery alone have high rates (up to 40%) of local and regional recurrence,2 prompting multiple trials that showed decreased risk of recurrence when radiation therapy is added to surgery.3
Despite these benefits of adjunctive radiation therapy for rectal cancer patients, there still remain treatment disparities among multiple groups.4,5 For example, higher volume “centers of excellence,” more routinely deliver radiation to patients with rectal cancer than lower volume centers,4,5 while Black patients are less likely to receive adjuvant chemotherapy and radiation therapy than White patients despite seemingly similar referral rates.5 To date, the role of rurality in receipt of radiation is less clear,6 as >90% of American College of Surgeons’ Rectal Cancer Program “centers of excellence” are located in cities of at least 50,000 people.7 Furthermore, it remains unclear how newer techniques, such as intensity modulated radiation therapy (IMRT), are being adopted/used across rural settings.
For patients with cancer residing in rural areas, reduced access to surgical care has been well-documented in many settings. For example, rural patients undergo fewer lung and colon cancer-directed surgeries than urban patients, and those rural patients who do undergo surgery tend to have worse outcomes than urban patients.8, 9, 10, 11 Although these disparities may reflect differences in patient underlying health or the socioeconomic determinants of their health, decreased access to adjuvant cancer therapies may further exacerbate the gap in urban-rural outcomes.12, 13, 14
Given the known disparities in use of surgical and radiation treatment for other cancer sites, we hypothesized that rural patients with rectal cancer would be less likely than urban patients to receive radiation. We sought to test this hypothesis by examining patterns of care among a nationwide sample of patients with rectal cancer. In addition, we explored the association between rural residence and various technical aspects involved in the use of radiation and surgical therapies.
Methods and Materials
Study population
We identified a cohort of Medicare beneficiaries with incident, nonmetastatic rectal cancer using a previously described modification15 of the algorithm described by Setoguchi et al16 (Fig. 1, Tables E1-3). We used fee-for-service Medicare claims from an observation window of April 1, 2016 to September 30, 2018, to identify the cohort. Beneficiaries were excluded if they were younger than 65 years and if they had end-stage renal disease, or evidence of stage IV rectal cancer. This observation period was preceded by a lookback period from October 1, 2015 to March 31, 2016 to exclude pre-existing cancers, including rectal cancers. To maximize sensitivity of detecting incident rectal cancers, subtotal rectal resections (such as transanal excision) were included in our initial cohort build. Given the uncertainty of treatment intent and staging associated with subtotal rectal resections, only patients who underwent a proctectomy were included in our surgical cohort analyses of adjuvant therapies, surgeon subspecialty, surgical modality, or surgical facility type.
Figure 1.
Cohort build to identify incident of nonmetastatic patients with rectal cancer. *Includes all United-States-residing fee-for-service Medicare beneficiaries with continuous enrollment in Medicare Parts A and B between October 1, 2015 and December 31, 2018 (or until death).
Exposure variable
Patient place of residence (at the level of United States Census tract) was categorized as either metropolitan (≥50,000 people), micropolitan (10,000-49,999), or small town/rural (<10,000 people), using rural urban commuting area codes. Due to small cell size concerns, the rural and small town categories were collapsed into a single category for analysis.
Outcome variables
The primary outcome among the full cohort was a composite defined as receipt of both proctectomy (Table E2) and radiation therapy (Table E4) within 180 days of diagnosis. For the subset of patients receiving proctectomy, additional outcomes were receipt of preop radiation, preop chemotherapy (Table E5), and minimally invasive surgery (MIS) (Table E6).
Secondary outcomes included receipt of any surgery (including nonproctectomy rectal surgeries such as transanal excision); receipt of any treatment (any surgery, radiation, or chemotherapy); surgeon's subspecialty; receipt of concurrent chemoradiation without surgery (as a proxy for “watchful waiting”17,18); academic medical center (AMC) or National Cancer Institute (NCI) designation; and radiation characteristics including fractionation and modality. When available, the surgeon's specialty was also abstracted from claims and defined as either colorectal surgery or surgical oncology. The hospital where the surgery was performed was stratified by AMC and whether or not the facility was an NCI-designated cancer center. For the subset of patients receiving radiation, we documented radiation characteristics including use of IMRT, number of fractions delivered, timing (before vs after surgery) and use of concurrent chemotherapy.
Covariates
The following were candidates for inclusion in adjusted regression models: age; race/ethnicity; Medicaid eligibility; disability as original reason for entitlement; previous myocardial infarction, cerebrovascular accident, or transient ischemic attack; comorbid diabetes, congestive heart failure, chronic obstructive pulmonary disease, liver disease, or renal disease. Race/ethnicity was derived from the Research Triangle Institute Race Code19 and collapsed into the following: non-Hispanic White, non-Hispanic Black, Hispanic, or Other (which is comprised of the following: Asian/Pacific Islander, American Indian/Alaskan Native, or Unknown). Analyses also adjusted for the overall health of the patient using the Hierarchical Condition Category (HCC) score,20 and the socioeconomic characteristics of the beneficiary's neighborhood using the area deprivation index, which is a geography-based composite measure index of socioeconomic status calculated at the 9-digit ZIP code level, using 17 measures of poverty, housing, and employment.19,21,22
Statistical analysis
Pearson χ2 tests and analysis of variance were used to test for differences in baseline covariates. The Kruskal-Wallis test was used to compare median number of radiation fractions. To account for loss to follow-up due to death, associations with the primary outcome (receipt of radiation and surgery within 180 days of diagnosis) were determined using Fine-Gray competing risks regression,23 and reported as an adjusted subhazard ratio; for this outcome, time to event was defined as days between diagnosis and later of the 2 components of the outcome (radiation and proctectomy). Logistic regression was used for outcomes with no loss to follow-up (preoperative radiation, preoperative chemotherapy, IMRT, MIS, and concurrent chemotherapy). Candidate covariates were included in regression models if they were determined to be associated with both the exposure (levels of rurality) and the outcome, using a conservative threshold of P < .2, and were dropped from final models if not significant at the P < .2 threshold. P <.05 was considered statistically significant.
Software
All statistical analyses were performed using Stata MP 17.0 statistical software (StataCorp LLC, College Station, TX).
Results
Patient characteristics
We identified 13,454 fee-for-service Medicare beneficiaries diagnosed with nonmetastatic rectal cancer over a 30-month period (Fig. 1). Of this cohort, 9797 (72.8%) were from metropolitan areas, 1813 (13.5%) from micropolitan areas, and 1844 (13.7%) from small town/rural areas (Table 1). In general, the patients were balanced in terms of mean age and sex. A greater proportion of small town/rural patients were white compared with metropolitan patients. Higher ADI and lower HCC scores were observed for small town/rural rectal cancer patients, reflecting lower socioeconomic status and relatively lower incidence of previously diagnosed medical comorbid conditions than urban beneficiaries.
Table 1.
Characteristics of patients according to rurality of patients’ residence (N = 13,454)
| Small town/rural (n = 1844) | Micropolitan (n = 1813) | Metropolitan (n = 9797) | P value | |
|---|---|---|---|---|
| Age, mean (SD) | 75.40 (6.9) | 75.27 (7.0) | 75.62 (7.3) | .10 |
| Age, no. (%), y | <.01 | |||
| 65-74 | 933 (50.6) | 919 (50.7) | 4931 (50.3) | |
| 75-84 | 711 (38.6) | 686 (37.8) | 3456 (35.3) | |
| 85+ | 200 (10.8) | 208 (11.5) | 1410 (14.4) | |
| Race/ethnicity, no. (%) | <.01 | |||
| White, non-Hispanic | 1657 (89.9) | 1636 (90.2) | 8315 (84.9) | |
| Black, non-Hispanic | 56 (3.0) | 74 (4.1) | 611 (6.2) | |
| Hispanic | 55 (3.0) | 63 (3.5) | 414 (4.2) | |
| Other | 76 (4.1) | 40 (2.2) | 457 (4.7) | |
| Sex, no. (%) | ||||
| Female | 847 (45.9) | 846 (46.7) | 4610 (47.1) | .67 |
| Past medical history, no. (%) | ||||
| Diabetes | 388 (21.0) | 384 (21.2) | 1940 (19.8) | .24 |
| Myocardial infarction | 17 (0.9) | 22 (1.2) | 89 (0.9) | .47 |
| CHF | 97 (5.3) | 123 (6.8) | 647 (6.6) | .08 |
| CVA/TIA | 29 (1.6) | 33 (1.8) | 186 (1.9) | .63 |
| COPD | 135 (7.3) | 172 (9.5) | 733 (7.5) | .01 |
| Liver disease | <11 | <11 | 14 (0.1) | |
| Kidney disease | 18 (1.0) | 21 (1.2) | 82 (0.8) | .38 |
| Fully dual-eligible, no. (%) | 138 (7.5) | 115 (6.3) | 627 (6.4) | .21 |
| Disabled, no. (%) | 211 (11.4) | 200 (11.0) | 864 (8.8) | <.01 |
| Area deprivation index, mean (SD) | 65.08 (19.5) | 61.27 (20.7) | 41.50 (26.6) | <.01 |
| HCC score, mean (SD) | 0.74 (0.6) | 0.78 (0.7) | 0.79 (0.7) | .02 |
| Receipt of treatment | ||||
| Days to any treatment, mean (SD) | 36.09 (27.3) | 36.32 (29.8) | 35.60 (29.1) | .67 |
| Any treatment within 180 d of Dx, no. (%) | 1239 (67.2) | 1197 (66.0) | 6475 (66.1) | .64 |
| Any surgery within 180 d of Dx, no. (%) | 772 (41.9) | 695 (38.3) | 3815 (38.9) | .04 |
| Proctectomy within 180 d of Dx, no. (%) | 613 (33.2) | 514 (28.4) | 2799 (28.6) | <.01 |
| Radiation within 180 d of Dx, no. (%) | 764 (41.4) | 746 (41.1) | 3901 (39.8) | .30 |
| Chemotherapy within 180 d of Dx, no. (%) | 714 (38.7) | 666 (36.7) | 3517 (35.9) | .07 |
| Proctectomy and radiation within 180 d of Dx, no. (%) | 329 (17.8) | 262 (14.5) | 1245 (13.7) | <.01 |
| Concurrent chemoradiation without surgery within 180 d, no. (%) | 240 (13.0) | 271 (14.9) | 1383 (14.1) | .24 |
Abbreviations: CHF = congestive heart failure; COPD = chronic obstructive pulmonary disease; CVA = cerebrovascular accident; Dx = diagnosis; HCC score = Hierarchical Condition Category; SD = standard deviation; TIA = transient ischemic attack.
Treatment characteristics
Of the 13,454 patients with rectal cancer, 5282 (39.3%) received a rectal surgery within 180 days of diagnosis. Of these, 1356 (25.7%) underwent nonproctectomy surgeries such as transanal excision, and 3926 (74.3%) underwent proctectomy (Fig. 1). The mean interval from diagnosis to proctectomy ranged from 81 to 87 days for all patients, varying only slightly across levels of rurality (Table 2). Fewer than half of all proctectomy patients (n = 1792, 45.6%) received radiation before their surgery, and 1334 (74.4%) of these preoperatively irradiated patients received chemotherapy concurrently. Fewer than 4% of proctectomy patients received radiation therapy postoperatively.
Table 2.
Treatment characteristics of patients undergoing proctectomy by rurality of patients’ residences (n = 3926)
| Small town/rural (n = 613) | Micropolitan (n = 514) | Metropolitan (n = 2799) | P value | |
|---|---|---|---|---|
| Preop radiation, no. (%) | 306 (49.9) | 242 (47.1) | 1244 (44.4) | .04 |
| Preop concurrent chemoradiation, no. (%)† | 238 (77.8) | 187 (77.3) | 909 (73.1) | .13 |
| IMRT, no. (%)† | 119 (38.9) | 116 (47.9) | 629 (50.6) | <.01 |
| No. of preop radiation fractions, median‡ | 28 | 28 | 28 | .35 |
| Postop radiation, no. (%) | 23 (3.8) | 20 (3.9) | 101 (3.6) | .95 |
| Preop chemotherapy, no. (%) | 272 (44.4) | 212 (41.2) | 1054 (37.7) | .01 |
| Postop chemotherapy, no. (%) | 108 (17.6) | 88 (17.1) | 486 (17.4) | .98 |
| Days from diagnosis to proctectomy, mean (SD) | 87.0 (56.9) | 82.9 (59.0) | 80.7 (58.6) | .05 |
| Minimally invasive surgery, no. (%) | 330 (53.8) | 273 (53.1) | 1725 (61.6) | <.01 |
| Surgeon's specialty* | <.01 | |||
| Colorectal surgeon/surgical oncologist, no. (%) | 269 (44.1) | 230 (45.0) | 1565 (56.1) | |
| General surgeon or other, no. (%) | 341 (55.9) | 281 (55.0) | 1227 (43.9) | |
| Hospital type* | <.01 | |||
| Academic and NCI-designated, no. (%) | 76 (12.6) | 59 (11.7) | 318 (11.6) | |
| Academic but not NCI-designated, no. (%) | 336 (55.6) | 247 (49.1) | 1632 (59.5) | |
| Neither academic nor NCI-designated, no. (%) | 192 (31.8) | 197 (39.2) | 793 (28.9) |
Abbreviations: IMRT = intensity modulated radiation therapy; NCI = National Cancer Institute.
Some data could not be determined for surgeon's specialty and for hospital type.
Denominator for these rows applies to preoperative radiation patients.
Median is calculated for those who received preoperative radiation.
Most proctectomies were performed at AMCs (n = 2668, 68.0%). The type of performing surgeon varied with geography (described in the next section). Although the surgeon's subspecialty was not associated with rates of neoadjuvant radiation (Table E7), surgery at an NCI-designated cancer center (vs non-NCI-centers) was associated with higher rates of preoperative radiation among proctectomy patients (55.0% vs 44.8%; P < .01; Table E8).
Geography and receipt of treatment
Rural patients received treatment slightly later after diagnosis compared with those in more populated areas (mean 87 days, vs 81-83 days). Proportionally more proctectomy patients from small/rural areas received preoperative radiation therapy than those from more populated areas, although this was not statistically significant (Table 2). Radiation fractionation did not vary across geography; we noted scant (<0.5%) use of short course schedules overall during the study period. No differences were noted across geography in the proportions receiving concurrent chemoradiation without surgery (13.0%, 14.9%, 14.1%, P = .24). Among patients who received preoperative radiation, proportionally more metropolitan and micropolitan patients received IMRT than small town/rural rectal cancer patients (50.6% vs 47.9% vs 38.9%; P < .01; Fig. 2).
Figure 2.
Treatment patterns for proctectomy patients by geographic location on univariate analysis χ2 test. For the preoperative radiation, preoperative chemotherapy, and MIS groups, the denominator was 3926. Denominator for the IMRT group was 1792. For the specialist surgeon group, defined as either colorectal surgeons or surgical oncologists, the denominator was 3913. Error bars represent standard errors. *P ≤ .05. Abbreviations: IMRT = intensity-modulated radiation therapy; MIS = minimally invasive surgery; pre-op = preoperative.
Metropolitan beneficiaries were more likely to undergo proctectomy from a surgical subspecialist than micropolitan or small town/rural beneficiaries (56.1% vs 45.0% vs 44.1%, P < .01). Proportionally more surgeries among metropolitan beneficiaries were coded as minimally invasive (61.6% vs 53.1% vs 53.8%, P < .01; Table 2, Fig. 2).
Multivariable regression results
Among the 13,454 patients who received a diagnosis of rectal cancer, residence across our 3 cohorts was not associated with likelihood of our composite outcome, receipt of both radiation and proctectomy within 180 days of rectal cancer diagnosis. However, when comparing small town/rural against metropolitan patients, there was a slightly increased likelihood (adjusted subhazard ratio, 1.15; 95% CI, 1.02-1.30) of rural patients’ receipt of this treatment (Table 3). Similarly, small town/rural patients were more likely to undergo preoperative radiation than their metropolitan counterparts (adjusted odds ratio [AOR], 1.21; 95% CI, 1.01-1.45), although there was no overall association across the 3 levels of rurality.
Table 3.
Association of rurality with receipt of radiation and surgery within 180 days and preoperative radiation therapy
| Receipt of radiation and proctectomy within 180 d* (N = 13,454) |
Preop radiation† (n = 3926) |
Preop chemotherapy‡ (n = 3926) |
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ASHR | 95% CI | P value | AOR | 95% CI | P value | AOR | 95% CI | P value | |||
| Place of residence Metropolitan | Reference | .05 | Reference | .10 | Reference | .01 | |||||
| Micropolitan | 0.99 | (0.88, 1.13) | 1.08 | (0.89, 1.31) | 1.14 | (0.94, 1.38) | |||||
| Small town/rural | 1.15 | (1.02, 1.30) | 1.21 | (1.01, 1.45 | 1.30 | (1.08, 1.56) | |||||
Abbreviations: AOR = adjusted odds ratio; ASHR = adjusted subhazard ratio; CI = confidence interval; HCC = Hierarchical Condition Category.
Final model adjusted for disability as original reason for entitlement, congestive heart failure, HCC score, age groups, race/ethnicity, and area deprivation index.
Final model adjusted for HCC score, age groups, and race/ethnicity.
Final model adjusted for HCC score and age groups.
Covariates assessed for inclusion included age, race/ethnicity, Medicaid eligibility, disability as original reason for entitlement, previous myocardial infarction and cerebrovascular attack/transient ischemic attack, comorbid diabetes, congestive heart failure, chronic obstructive pulmonary disease, liver disease, renal disease, HCC score, and area deprivation index for patient residence. Candidate covariates not associated (using conservative threshold of P < .2) with both place of residence/geography and outcome (ie, nonconfounders) were not included in final models.
Levels of rurality were not associated with differential receipt of concurrent chemotherapy (Table 4); however, as rurality increased, patients were more likely to receive sequential, neoadjuvant chemotherapy. Among the 3926 proctectomy patients who received preoperative radiation, small town/rural beneficiaries were least likely to receive IMRT (AOR, 0.62; 95% CI, 0.48-0.80) or receive MIS (AOR, 0.80; 95% CI, 0.66-0.97), compared with metropolitan patients.
Table 4.
Association of rurality with type of surgery and features of radiation therapy delivery
| IMRT* (n = 1792) |
Concurrent chemotherapy† (n = 1792) |
Minimally invasive surgery‡ (n = 3926) |
|||||||
|---|---|---|---|---|---|---|---|---|---|
| AOR | 95% CI | P value | AOR | 95% CI | P value | AOR | 95% CI | P value | |
| Place of residence Metropolitan | Reference | <.01 | Reference | .15 | Reference | <.01 | |||
| Micropolitan | 0.90 | (0.68, 1.19) | 1.25 | (0.90, 1.73) | 0.78 | (0.64,0.94) | |||
| Small town/rural | 0.62 | (0.48, 0.80) | 1.28 | (0.95, 1.72) | 0.80 | (0.66, 0.97) | |||
Abbreviations: AOR = adjusted odds ratio; CI = confidence interval; HCC = Hierarchical Condition Category; IMRT = intensity modulated radiation therapy.
Final model adjusted for: none.
Final model adjusted for HCC score.
Final model adjusted for HCC score, age groups, and area deprivation index.
Covariates assessed for inclusion included age, race/ethnicity, Medicaid eligibility, disability as original reason for entitlement, previous myocardial infarction and cerebrovascular attack/transient ischemic attack, comorbid diabetes, congestive heart failure, chronic obstructive pulmonary disease, liver disease, renal disease, HCC score, and area deprivation index for patient residence. Candidate covariates not associated (using conservative threshold of P < .2) with both place of residence/geography and outcome (ie, nonconfounders) were not included in final models.
Discussion
In this study using national Medicare claims data, we analyzed the treatment of 3926 elderly patients who underwent proctectomy for rectal cancer, of whom 1792 (45.6%) also received radiation therapy. When analyzing our full cohort, we found that, after adjusting for sociodemographic and clinical characteristics, small town and rural patients were slightly more likely than more urban-dwelling patients to receive both radiation and proctectomy within 180 days of diagnosis. Of those patients who received proctectomy, >95% of radiation courses were received before surgery, across the rural-urban continuum. The vast majority of courses were traditional “long course” chemoradiation schedules and the only difference we detected in terms of the radiation modality regards use of IMRT, which was used least often for small town and rural patients.
Contrary to our hypothesis that rural patients with rectal surgery would be less likely to undergo radiation than urban dwellers, we did not detect an association between levels of rurality and receipt of preoperative radiation therapy. Although rural areas may have fewer radiation resources,12,24 it is possible that rural patients are referred to centers where surgeons are more likely to recommend neoadjuvant therapy. It is also possible that rural residents are more tolerant of long commutes for work, recreation, and medical care,25 and therefore more willing to adhere to treating surgeons’ recommendations regarding neoadjuvant therapy.
Although overall receipt and timing of radiation therapy did not differ across the rural-urban continuum, we found the use of IMRT varied across geography, as reported in other settings.26,27 Nonetheless, the routine use of IMRT for rectal cancer remains a source of ongoing controversy in the radiation oncology community28,29 and recent guidelines do not recommend it given mixed efficacy data30, 31, 32 despite dosimetric studies showing reduced dose to small bowel, bladder, and bone marrow.33, 34, 35, 36 Similarly, we found that surgeon training and surgical modality varied across geography, with rural and small town patients least likely to receive care from subspecialty-trained surgeons or minimally invasive surgical approaches, trends observed in other disease settings.37 In contrast to the lack of consensus surrounding use of IMRT, data supporting MIS affirms quicker bowel recovery, decreased postoperative pain, improved cosmesis, and shorter length of hospital stay.38 Reasons for the disparity in its use may be explained by lower supply of rural specialty surgeons or access to equipment and technology more readily available at high-volume, urban surgical centers.39,40
There are limitations of this study, which should be considered. First, we acknowledge that our surgery rates appear low. There are inherent limitations in working with Medicare claims data; namely, the patients in our cohort are by definition elderly, and we do not have details regarding cancer staging (beyond notation of metastatic status), treatment intent, or radiation dose. A recent National Cancer Database analysis described rectal cancer surgery rates in the range of 60% to 70%.41 Other registry studies with access to staging information showed similar operative rates as well.42, 43, 44 Medicare beneficiaries are older, have more comorbid illnesses, and their diagnoses lack clarity in terms of stage, accuracy of diagnosis, and treatment intent, and therefore our results may not be generalizable to other populations. Despite low surgery rates in this unselected cohort, receipt of radiation among surgery patients should not vary with patient health, given that radiation is administered in a variety of settings and does not depend on patient age or functional status to the same extent as surgery. In other words, patients healthy enough for surgery are in nearly all cases healthy enough for radiation. Finally, subgroups within the rural and small town areas contained very few patients. This led us to combine these 2 groups, thus losing some granularity and ability to discern whether forces that drive medical decision making in small towns differ from those in more rural settings.
Conclusion
Using nationwide data, we found that Medicare beneficiaries with rectal cancer who live in rural areas and small towns are more likely to receive standard of care surgery and radiation than patients who live in more metropolitan areas. Rural radiation patients were less likely to be treated with IMRT. Lastly, there appeared to be a similar utilization of radiation modalities and time to radiation treatment regardless of geographic differences. Future studies should explore underlying causes for this observed geographic variation.
Disclosures
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Footnotes
Sources of support: This study was supported with Project Grant R01CA248470.
Research data are not available at this time.
Supplementary material associated with this article can be found in the online version at doi:10.1016/j.adro.2023.101286.
Appendix. Supplementary materials
References
- 1.American Cancer Society. Key statistics for colorectal cancer. Available at: https://www.cancer.org/cancer/colon-rectal-cancer/about/key-statistics.html. Accessed November 2, 2021.
- 2.Gunderson LL, Sosin H. Areas of failure found at reoperation (second or symptomatic look) following "curative surgery" for adenocarcinoma of the rectum. Clinicopathologic correlation and implications for adjuvant therapy. Cancer. 1974;34:1278–1292. doi: 10.1002/1097-0142(197410)34:4<1278::aid-cncr2820340440>3.0.co;2-f. [DOI] [PubMed] [Google Scholar]
- 3.Group CCC. Adjuvant radiotherapy for rectal cancer: A systematic overview of 8,507 patients from 22 randomised trials. Lancet. 2001;358:1291–1304. doi: 10.1016/S0140-6736(01)06409-1. [DOI] [PubMed] [Google Scholar]
- 4.Morris AM, Wei Y, Birkmeyer NJ, Birkmeyer JD. Racial disparities in late survival after rectal cancer surgery. J Am Coll Surg. 2006;203:787–794. doi: 10.1016/j.jamcollsurg.2006.08.005. [DOI] [PubMed] [Google Scholar]
- 5.Morris AM, Billingsley KG, Hayanga AJ, Matthews B, Baldwin LM, Birkmeyer JD. Residual treatment disparities after oncology referral for rectal cancer. J Natl Cancer Inst. 2008;100:738–744. doi: 10.1093/jnci/djn396. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Onega T, Duell EJ, Shi X, Wang D, Demidenko E, Goodman D. Geographic access to cancer care in the US. Cancer. 2008;112:909–918. doi: 10.1002/cncr.23229. [DOI] [PubMed] [Google Scholar]
- 7.American College of Surgeons. Hospital and facilities centers of excellence 2023 [rectal program]. Available at: https://www.facs.org/hospital-and-facilities/?searchTerm=&institution=Rectal&page=3. Accessed May 16, 2023.
- 8.Atkins GT, Kim T, Munson J. Residence in rural areas of the United States and lung cancer mortality. Disease incidence, treatment disparities, and stage-specific survival. Ann Am Thorac Soc. 2017;14:403–411. doi: 10.1513/AnnalsATS.201606-469OC. [DOI] [PubMed] [Google Scholar]
- 9.Chow CJ, Al-Refaie WB, Abraham A, et al. Does patient rurality predict quality colon cancer care? A population-based study. Dis Colon Rectum. 2015;58:415–422. doi: 10.1097/DCR.0000000000000173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Gruber K, Soliman AS, Schmid K, Rettig B, Ryan J, Watanabe-Galloway S. Disparities in the utilization of laparoscopic surgery for colon cancer in rural Nebraska: A call for placement and training of rural general surgeons. J Rural Health. 2015;31:392–400. doi: 10.1111/jrh.12120. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Loehrer AP, Colla CH, Wong SL. Rural cancer care: The role of space and place in care delivery. Ann Surg Oncol. 2020;27:1724–1725. doi: 10.1245/s10434-020-08392-y. [DOI] [PubMed] [Google Scholar]
- 12.Longacre CF, Neprash HT, Shippee ND, Tuttle TM, Virnig BA. Evaluating travel distance to radiation facilities among rural and urban breast cancer patients in the Medicare population. J Rural Health. 2020;36:334–346. doi: 10.1111/jrh.12413. [DOI] [PubMed] [Google Scholar]
- 13.Spees LP, Wheeler SB, Varia M, et al. Evaluating the urban-rural paradox: The complicated relationship between distance and the receipt of guideline-concordant care among cervical cancer patients. Gynecol Oncol. 2019;152:112–118. doi: 10.1016/j.ygyno.2018.11.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Bhatia S, Landier W, Paskett ED, et al. Rural-urban disparities in cancer outcomes: opportunities for future research. J Natl Cancer Inst. 2022;114:940–952. doi: 10.1093/jnci/djac030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Bronson MR, Kapadia NS, Austin AM, et al. Leveraging linkage of cohort studies with administrative claims data to identify individuals with cancer. Med Care. 2018;56:e83–e89. doi: 10.1097/MLR.0000000000000875. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Setoguchi S, Solomon DH, Glynn RJ, Cook EF, Levin R, Schneeweiss S. Agreement of diagnosis and its date for hematologic malignancies and solid tumors between medicare claims and cancer registry data. Cancer Causes Control. 2007;18:561–569. doi: 10.1007/s10552-007-0131-1. [DOI] [PubMed] [Google Scholar]
- 17.Habr-Gama A, Sabbaga J, Gama-Rodrigues J, et al. Watch and wait approach following extended neoadjuvant chemoradiation for distal rectal cancer: Are we getting closer to anal cancer management? Dis Colon Rectum. 2013;56:1109–1117. doi: 10.1097/DCR.0b013e3182a25c4e. [DOI] [PubMed] [Google Scholar]
- 18.Habr-Gama A, Gama-Rodrigues J, São Julião GP, et al. Local recurrence after complete clinical response and watch and wait in rectal cancer after neoadjuvant chemoradiation: Impact of salvage therapy on local disease control. Int J Radiat Oncol Biol Phys. 2014;88:822–828. doi: 10.1016/j.ijrobp.2013.12.012. [DOI] [PubMed] [Google Scholar]
- 19.Rural-Urban Commuting Area Codes. USDA Economic Research Service. Available at: https://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes/. Accessed November 2, 2021.
- 20.Eicheldinger C, Bonito A. More accurate racial and ethnic codes for Medicare administrative data. Health Care Financ Rev. 2008;29:27–42. [PMC free article] [PubMed] [Google Scholar]
- 21.Centers for Medicare & Medicaid Services’ Office of Research, Development, and Information. Evaluation of the CMS-HCC risk adjustment model. Available at:http://www.cms.gov/Medicare/Health-Plans/MedicareAdvtgSpecRateStats/downloads/evaluation_risk_adj_model_2011.pdf. Accessed November 2, 2021.
- 22.United States Department of Agriculture, Economic Research Service. Rural-urban commuting area codes. Available at:https://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes/. Accessed November 2, 2021.
- 23.Fine J, Gray R.A. Proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94:496–509. [Google Scholar]
- 24.Maroongroge S, Wallington DG, Taylor PA, et al. Geographic access to radiation therapy facilities in the United States. Int J Radiat Oncol Biol Phys. 2022;112:600–610. doi: 10.1016/j.ijrobp.2021.10.144. [DOI] [PubMed] [Google Scholar]
- 25.Mattson J. Transportation, distance, and health care utilization for older adults in rural and small urban areas. Transport Res Rec. 2011;265 [Google Scholar]
- 26.Grant SR, Smith BD, Likhacheva AO, et al. Provider variability in intensity modulated radiation therapy utilization among Medicare beneficiaries in the United States. Pract Radiat Oncol. 2018;8:e329–e336. doi: 10.1016/j.prro.2018.02.004. [DOI] [PubMed] [Google Scholar]
- 27.Valle LF, Chu FI, Yoon SM, et al. Provider-level variation in treatment planning of radiation oncology procedures in the United States. JCO Oncol Pract. 2021;17:e1905–e1912. doi: 10.1200/OP.20.00441. [DOI] [PubMed] [Google Scholar]
- 28.Jabbour SK, Patel S, Herman JM, et al. Intensity-modulated radiation therapy for rectal carcinoma can reduce treatment breaks and emergency department visits. Int J Surg Oncol. 2012;2012 doi: 10.1155/2012/891067. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Wegner RE, Abel S, White RJ, Horne ZD, Hasan S, Kirichenko AV. Trends in intensity-modulated radiation therapy use for rectal cancer in the neoadjuvant setting: A National Cancer Database analysis. Radiat Oncol J. 2018;36:276–284. doi: 10.3857/roj.2018.00465. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Wo JY, Anker CJ, Ashman JB, et al. Radiation therapy for rectal cancer: Executive summary of an ASTRO Clinical Practice Guideline. Pract Radiat Oncol. 2021;11:13–25. doi: 10.1016/j.prro.2020.08.004. [DOI] [PubMed] [Google Scholar]
- 31.Wee CW, Kang HC, Wu HG, et al. Intensity-modulated radiotherapy versus three-dimensional conformal radiotherapy in rectal cancer treated with neoadjuvant concurrent chemoradiation: A meta-analysis and pooled-analysis of acute toxicity. Jpn J Clin Oncol. 2018;48:458–466. doi: 10.1093/jjco/hyy029. [DOI] [PubMed] [Google Scholar]
- 32.Regnier A, Ulbrich J, Münch S, et al. Comparative analysis of efficacy, toxicity, and patient-reported outcomes in rectal cancer patients undergoing preoperative 3D conformal radiotherapy or VMAT. Front Oncol. 2017;7:225. doi: 10.3389/fonc.2017.00225. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Arbea L, Ramos LI, Martínez-Monge R, Moreno M, Aristu J. Intensity-modulated radiation therapy (IMRT) versus. 3D conformal radiotherapy (3DCRT) in locally advanced rectal cancer (LARC): Dosimetric comparison and clinical implications. Radiat Oncol. 2010;5:17. doi: 10.1186/1748-717X-5-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Dapper H, Rodríguez I, Münch S, et al. Impact of VMAT-IMRT compared to 3D conformal radiotherapy on anal sphincter dose distribution in neoadjuvant chemoradiation of rectal cancer. Radiat Oncol. 2018;13:237. doi: 10.1186/s13014-018-1187-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Samuelian JM, Callister MD, Ashman JB, Young-Fadok TM, Borad MJ, Gunderson LL. Reduced acute bowel toxicity in patients treated with intensity-modulated radiotherapy for rectal cancer. Int J Radiat Oncol Biol Phys. 2012;82:1981–1987. doi: 10.1016/j.ijrobp.2011.01.051. [DOI] [PubMed] [Google Scholar]
- 36.Yang TJ, Oh JH, Son CH, et al. Predictors of acute gastrointestinal toxicity during pelvic chemoradiotherapy in patients with rectal cancer. Gastrointest Cancer Res. 2013;6:129–136. [PMC free article] [PubMed] [Google Scholar]
- 37.Patel R, Pant K, Patel KS, Merchant AM. Alvarez-Downing MM. Association of hospital factors and socioeconomic status with the utilization of minimally invasive surgery for colorectal cancer over a decade. Surg Endosc. 2022;36:3750–3762. doi: 10.1007/s00464-021-08690-w. [DOI] [PubMed] [Google Scholar]
- 38.Schneider MA, Gero D, Müller M, Horisberger K, Rickenbacher A, Turina M. Inequalities in access to minimally invasive general surgery: A comprehensive nationwide analysis across 20 years. Surg Endosc. 2021;35:6227–6243. doi: 10.1007/s00464-020-08123-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Aboagye JK, Kaiser HE, Hayanga AJ. Rural-urban differences in access to specialist providers of colorectal cancer care in the United States: A physician workforce issue. JAMA Surg. 2014;149:537–543. doi: 10.1001/jamasurg.2013.5062. [DOI] [PubMed] [Google Scholar]
- 40.Chioreso C, Gao X, Gribovskaja-Rupp I, et al. Hospital and surgeon selection for medicare beneficiaries with stage II/III rectal cancer: The role of rurality, distance to care, and colonoscopy provider. Ann Surg. 2021;274:e336–ee44. doi: 10.1097/SLA.0000000000003673. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Emile SH, Horesh N, Freund MR, et al. Trends in the characteristics, treatment, and outcomes of rectal adenocarcinoma in the US from 2004 to 2019: A National Cancer Database Analysis. JAMA Oncol. 2023;9:355–364. doi: 10.1001/jamaoncol.2022.6116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Del Vecchio NJ, Schlichting JA, Chioreso C, et al. Guideline-recommended chemoradiation for patients with rectal cancer at large hospitals: A trend in the right direction. Dis Colon Rectum. 2019;62:1186–1194. doi: 10.1097/DCR.0000000000001452. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Dutta SW, Alonso CE, Jones TC, Waddle MR, Janowski EM, Trifiletti DM. Short-course versus long-course neoadjuvant therapy for non-metastatic rectal cancer: Patterns of care and outcomes from the national cancer database. Clin Colorectal Cancer. 2018;17:297–306. doi: 10.1016/j.clcc.2018.07.008. [DOI] [PubMed] [Google Scholar]
- 44.Sineshaw HM, Jemal A, Thomas CR, Mitin T. Changes in treatment patterns for patients with locally advanced rectal cancer in the United States over the past decade: An analysis from the National Cancer Data Base. Cancer. 2016;122:1996–2003. doi: 10.1002/cncr.29993. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.


