Introduction: Both colon cancer and dementia are prevalent among the elderly and have a high risk of cooccurrence. Previous studies found that patients with dementia were treated less aggressively. In this study, we hypothesized that presence of preexisting dementia was associated with worse survival for stage III colon cancer patients, and that postoperative chemotherapy was on the causal pathway.

Methods: We defined preexisting dementia in Surveillance Epidemiology and End Results Medicare data through either a formal diagnosis or a prescription for dementia drugs or both before the diagnosis of cancer. We applied multivariable Cox regression to estimate the effect of preexisting dementia on survival, adjusting for demographic factors, tumor characteristics, and receipt of chemotherapy. We assessed mediating effects in the context of the counterfactual framework using the accelerated failure time model.

Results: There were 4,573 patients diagnosed with stage III colon cancer between 2007 and 2009 identified. A preexisting diagnosis of dementia significantly increased the risk of death by 45% (HR = 1.45, 95% CI: 1.29–1.63). Patients with either a formal diagnosis of dementia or a related prescription had significantly lower cause-specific survival than their cognitively healthy counterparts. Receipt of chemotherapy was a significant mediator on the causal pathway. The effect of presence of dementia was mediated by receipt of chemotherapy by 13% for preexisting dementia.

Conclusions: Preexisting dementia is significantly associated with worse survival for stage III colon cancer patients, and its deleterious effect is partially explained by decreased likelihood of postoperative chemotherapy receipt.

Impact: This is the first study that provides estimate of the mediating effect of diminished chemotherapy in patients with stage III colon cancer and dementia, simultaneously demonstrating the cancer-specific survival benefit of chemotherapy in the presence of dementia. Cancer Epidemiol Biomarkers Prev; 26(10); 1558–63. ©2017 AACR.

This article is featured in Highlights of This Issue, p. 1475

Both dementia and colon cancer are prevalent among people ages 65 and older. Colon cancer is the third most common and the second leading cause of cancer-related death in the United States. According to national statistics, there will be a total of 95,270 new colon cancer cases diagnosed and 49,190 attributable deaths in 2016 (1). According to the World Health Organization, 1 in every 8 people age 65 and older and 1 in every 2.5 people age 85 and over on average will be affected by dementia (2). The incidence of both colon cancer and dementia increases with age, resulting in a high age-related probability of cooccurrence that complicates both outcomes and treatment decisions.

Survival after the diagnosis of colon cancer has improved continuously since the 1970s. This improvement is prominent among those with regional stage disease, where it reflects improvement in adjuvant chemotherapy for colon cancer that has spread to regional lymph nodes (stage III; ref. 3). Although large clinical trials demonstrate that adjuvant fluoropyrimidine and oxaliplatin-based chemotherapy reduces the risk of recurrence and subsequently improves survival in patients with stage III colon cancer (4, 5), these treatments are associated with significant toxicities that result in challenging risk versus benefit assessments for older patients (6). Nonetheless, the provision of fluoropyrimidine-based adjuvant chemotherapy for eligible patients with stage III colon cancer has been strongly recommended since at least 1990 (7).

Between 1990 and 2040, the U.S. elderly population is expected to grow from 31.6 to 68.1 million (8). Demographic projections estimate that by 2030, 22% of the U.S. population will be age 65 and older (9), which will contribute a 60% increase in cancer incidence (10). As the population ages, oncologists will increasingly encounter cancer patients with cognitive impairment. Given the high prevalence of cognitive impairment in older adults with cancer, understanding the overall extent to which dementia adversely affects colon cancer survival outcomes in this elderly group holds particular clinical and public health relevance.

There have been a number of studies on cancer treatment and outcomes of these cognitively impaired cancer patients. For example, cognitively impaired cancer patients are more likely to have lower treatment tolerance (11) and receive less curative treatment, both of which contribute to a 20% to 50% increase in mortality risk (10, 12–15). However, variations in study sample, methodology, and case definitions limit the generalizability of findings from all these existing studies to the U.S. elderly population. Moreover, there is no study to our knowledge that has examined the relationship between dementia and survival after diagnosis of nonmetastatic colon cancer, with treatment choice as a possible mediating factor.

A prior study used Surveillance Epidemiology and End Results (SEER)-Medicare data for patients diagnosed from 1993 to 2005 to address the effect of dementia on treatment and survival for colon cancer patients (12); however, because Medicare Part D data were not available during the study period, the authors could not use medication history as supplementary data to identify patients with dementia. So far there are four FDA-approved drug treatments for dementia that may temporarily improve symptoms (donepezil, galantamine, memantine, and rivastigmine). Tacrine was also approved for dementia treatment during the study period but withdrawn in 2013 in the United States. All of them can be prescribed to patients with symptoms of cognitive impairment with or without a formal diagnosis of dementia. There are no other currently recognized indications for the use of these drugs. Therefore, we believe that by combining medication data with diagnosis code, the sensitivity for physician-recognized dementia or cognitive impairment would be increased, while retaining specificity. In this study, we evaluated the effect of dementia on survival among stage III colon cancer patients who had received initial surgical treatment using the improved algorithm in dementia identification and then examined the causal relationship between adjuvant chemotherapy and survival outcome for these cognitively impaired colon cancer patients.

This was a retrospective cohort study that identified patients who were diagnosed with stage III colon cancer in 2007 to 2009 using the SEER-Medicare linked databases (described in detail elsewhere; ref. 16). Because the data were deidentified, the project was exempted from the UC Davis Institutional Review Board. With permission from the IMS Health, Medicare files received and used for this study included the Medicare Provider Analysis and Review (MedPAR) file; the inpatient, outpatient, NCH (physician/supplier), home health agency (HHA), and durable medical equipment (DME) claims files; and the Medicare Part D file, in accordance with their requirements for data protection and confidentiality. By signing the Data Use Agreement with the IMS, the data were allowed to be released without obtaining authorization from individual patients. Only patients for whom colon cancer was the first or only cancer diagnosis and those who were age 65 years or above were eligible. Patients with death certificate only or diagnosis at autopsy were excluded from the analysis.

The primary predictor was the presence of preexisting dementia, which was identified through either a formal diagnosis in the claims data (inpatient, outpatient, physician files, and HHA files) or a medication record in the Part D data. In the claims data, the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes were used. Codes for Alzheimer disease and related dementia were 290.40 to 290.43, 331.0, 331.1, 331.11, 331.19, 331.82, 046.11, 046.19, 292.82, 333.4, 290.10 to 290.13, 290.0, 290.20, 290.21, 290.3, 331.2, 331.9, 290.8, 290.9, 294.10, 294.11, 294.20, 294.21, 294.1, 294.8, and 797, and 331.83 for mild cognitive impairment (12). In the Part D data, patients with a prescription for any of the four FDA-approved dementia drugs (donepezil, galantamine, memantine, and rivastigmine) plus tacrine were identified as dementia cases.

Covariates include patient's demographic characteristics (age, gender, race, marital status, insurance types, median income for census tract, percentage of persons 25+ with less than 12 years of education in the census tract, and urban/rural recode), tumor grade, and comorbidities. Marital status was categorized into three levels: ”married” included patients who were married; ”single” included patients who were never married, separated, divorced, or widowed; and ”other” marital status included patients who had a domestic partner or with unknown marital status. Insurance coverage was defined as private or government (including managed care and Medicare with supplement), Medicaid or low income, Medicare, insured not otherwise specified, and uninsured. The median income for census tract and the percentage of persons 25+ with less than 12 years of education in the census tract were used as criteria for evaluation of patient's social economic status, and they were categorized as tertiles. Comorbidity was derived from diagnosis codes in outpatient and inpatient claims during a time window of 1 year before the diagnosis of colon cancer for comorbidity computation (17). Number of comorbidities was measured using Charlson comorbidity index (CCI; refs. 18, 19), modified to exclude dementia. CCI was categorized into “none,” “one,” and “two or more.” Receipt of chemotherapy was identified by HCPCS codes 964XX, 96500 to 96549, Q0083 to Q0085, J9000 to 9999, G0345 to G0351, G0353 to G0363, J0640, 51720, or ICD-9 codes V581, V662, V672 or 99.25. The 11-digit National Drugs Codes (NDC) in the DME file were used to capture the usage of orally administered chemotherapy, including 000041100xx, 000041101xx, 548684143xx, 548685260xx, and 545695717xx.

χ2 tests were used to determine whether the distributions of covariates were significantly different between patients with and without the presence of dementia. The primary analysis compared the survival of patients with preexisting dementia (defined as either formal diagnosis or prescribed medication or both) with those with no evidence of dementia before the diagnosis of cancer. Time from the diagnosis of tumor to death or the end of 2009 was considered as time to event. A person was considered censored if he or she died of other diseases during the study period. Multivariable Cox regression analyses were performed to assess the cancer-specific risk of death, assuming an independent censoring mechanism. Two models were constructed for distinct comparison purposes. Model 1 aimed to estimate the overall effect of preexisting dementia on survival. Model 2, a sensitivity analysis, aimed to further confirm the effect of preexisting dementia on survival but among a more restrictive group of patients who had both a formal diagnosis of and a medication prescription for dementia, as well as to assess the independent effects of source of dementia diagnosis. Covariates included demographic characteristics and tumor grade, receipt of chemotherapy, and number of comorbidities. Secondary analyses examined the effect of coexisting dementia on cancer survival (that is, the evidence of dementia could present before, concurrent with, or after the diagnosis of cancer).

The mediating effect of chemotherapy was estimated through a Weibull accelerated failure time (AFT) model, to allow estimation of as well as testing for mediation, through a counterfactual approach (20). In the AFT model, the estimated effect is the proportionate change in the mean survival time: a reduction, or less than 1, for a deleterious covariate, and an increase, or greater than 1, for a protective covariate. This is in contrast to the proportional hazards model, where the effect of a deleterious covariate is to increase the hazard of death (effect greater than 1). The Weibull distribution offers flexibility to allow for hazards that may increase, decrease, or remain constant after diagnosis. The mediation effect is estimated from two quantities that can be computed through the AFT: the natural direct effect (NDE) and natural indirect effect (NIE). The NDE is the estimated impact on the mean survival time of a person simply having dementia but treated just like a person without dementia, compared with a person without dementia. The NIE is the estimated effect on the mean survival time of current chemotherapy practice for people with dementia, compared with the hypothetical situation where a person with dementia is as likely to get chemotherapy as a person without dementia (effect is less than 1 if current practice is deleterious). The NDE thus captures decrease in survival due to having dementia, whereas the NIE captures the decrease in survival time due to someone with dementia potentially not receiving more aggressive treatment. The mediation effect of decreased use of chemotherapy in the presence of dementia was estimated by the following formula (21):

The denominator represents the total impact of having dementia on survival, whereas the numerator represents that portion just due to being more likely to receive chemotherapy. A well-established SAS macro for estimation of NDE and NIE was implemented in this study (its manual can be accessed at http://links.lww.com/EDE/A877; ref. 22). SEs were estimated by the delta method.

A total of 4,573 patients diagnosed with stage III colon cancer from 2007 to 2009 were identified in SEER-Medicare data, of whom 3,903 had valid dates associated with both diagnosis of dementia and cancer, and were included for the following analyses. We identified 575 patients with preexisting dementia using either a recorded diagnosis or a prescribed antidementia medication. Patient demographics, number of comorbidities, tumor grade, and receipt of chemotherapy are described in Table 1. About 22% of the patients were over age 84. More than half of the patients were female. A majority of the patients were non-Hispanic whites, with smaller numbers of Hispanics, Asian/Pacific Islanders, and non-Hispanic blacks. Almost all patients resided in a metropolitan area (61% for big metro area and 25% for metro area). A majority of the patients were married and fully covered by either Medicare (62%) or private or government-based insurance (33%). Forty percent of the patients had no comorbidities. Fewer than half of the patients received chemotherapy.

Table 1.

Demographic factors, tumor characteristics, and receipt of postoperative chemotherapy for patients with stage III colon cancer by their cognitive status (preexisting dementia), 2007–2009, N (%)

Dementia
VariablesTotal (N = 3,903)No (n = 3,328)Yes (n = 575)P
Age    <0.001 
 65–84 3,060 (78.4) 2,713 (81.5) 347 (60.4)  
 84+ 843 (21.6) 615 (18.5) 228 (39.7)  
Gender    0.023 
 Male 1,524 (39.1) 1,324 (39.8) 200 (34.8)  
 Female 2,379 (60.9) 2,004 (60.2) 375 (65.2)  
Race    0.197 
 White 3,112 (79.7) 2,661 (80.0) 451 (78.4)  
 Black 389 (10.0) 322 (9.7) 67 (11.7)  
 Hispanic 73 (1.9) 62 (1.9) 11 (1.9)  
 Asian 193 (4.9) 159 (4.8) 34 (5.9)  
 Unknown/other 136 (3.5) 124 (3.6) 12 (2.1)  
Marital status    0.002 
 Married 3,470 (88.9) 2,976 (89.4) 494 (85.9)  
 Single 307 (7.9) 241 (7.2) 66 (11.5)  
 Unknown 126 (3.2) 111 (3.3) 15 (2.6)  
Insurance types    <0.001 
 Insured, NOS 79 (2.0) 67 (1.9) 12 (2.1)  
 Medicaid/low income 40 (1.0) 33 (1.0) 7 (1.2)  
 Medicare 2,409 (61.7) 1,985 (61.1) 424 (73.7)  
 Private/government 1,301 (33.3) 1,176 (34.0) 125 (21.7)  
 Not insured 6 (0.2) 5 (0.2) 1 (0.2)  
 Unknown 57 (1.5) 51 (1.8) 6 (1.0)  
 Missing 11 (0.3) 11 (0.3) 0 (0.0)  
Median income    0.454 
 Low 1,331 (34.5) 1,124 (34.1) 207 (36.6)  
 Median 1,239 (32.1) 1,068 (32.4) 171 (30.2)  
 High 1,288 (33.4) 1,100 (33.4) 188 (33.2)  
Less than 12 years education    0.060 
 Low percentage 1,231 (31.9) 1,068 (32.4) 163 (28.8)  
 Middle percentage 1,270 (32.9) 1,090 (33.1) 180 (31.8)  
 High percentage 1,357 (35.2) 1,134 (34.5) 223 (39.4)  
Urban/rural recode    0.930 
 Big Metro 2,361 (60.5) 2,020 (60.7) 341 (59.3)  
 Metro 980 (25.1) 828 (24.9) 152 (26.4)  
 Urban 168 (4.3) 142 (4.3) 26 (4.5)  
 Less urban 317 (8.1) 271 (8.2) 46 (8.0)  
 Rural 76 (2.0) 66 (2.0) 10 (1.7)  
Grade    0.689 
 Grade I 196 (5.0) 162 (4.9) 34 (5.9)  
 Grade II 2,383 (61.1) 2,046 (61.5) 337 (58.6)  
 Grade III 1,110 (28.4) 938 (28.2) 172 (29.9)  
 Grade IV 119 (3.1) 101 (3.0) 18 (3.1)  
 Unknown 95 (2.4) 81 (2.4) 14 (2.4)  
CCI    <0.001 
 No comorbidity 1,608 (41.2) 1,443 (43.4) 165 (28.7)  
 1 956 (24.5) 814 (24.5) 142 (24.7)  
 2+ 1,337 (34.3) 1,069 (32.1) 268 (46.6)  
Chemotherapy    <0.001 
 No 2,523 (64.6) 2,078 (62.4) 445 (77.4)  
 Yes 1,380 (35.4) 1,250 (37.6) 130 (22.6)  
Dementia
VariablesTotal (N = 3,903)No (n = 3,328)Yes (n = 575)P
Age    <0.001 
 65–84 3,060 (78.4) 2,713 (81.5) 347 (60.4)  
 84+ 843 (21.6) 615 (18.5) 228 (39.7)  
Gender    0.023 
 Male 1,524 (39.1) 1,324 (39.8) 200 (34.8)  
 Female 2,379 (60.9) 2,004 (60.2) 375 (65.2)  
Race    0.197 
 White 3,112 (79.7) 2,661 (80.0) 451 (78.4)  
 Black 389 (10.0) 322 (9.7) 67 (11.7)  
 Hispanic 73 (1.9) 62 (1.9) 11 (1.9)  
 Asian 193 (4.9) 159 (4.8) 34 (5.9)  
 Unknown/other 136 (3.5) 124 (3.6) 12 (2.1)  
Marital status    0.002 
 Married 3,470 (88.9) 2,976 (89.4) 494 (85.9)  
 Single 307 (7.9) 241 (7.2) 66 (11.5)  
 Unknown 126 (3.2) 111 (3.3) 15 (2.6)  
Insurance types    <0.001 
 Insured, NOS 79 (2.0) 67 (1.9) 12 (2.1)  
 Medicaid/low income 40 (1.0) 33 (1.0) 7 (1.2)  
 Medicare 2,409 (61.7) 1,985 (61.1) 424 (73.7)  
 Private/government 1,301 (33.3) 1,176 (34.0) 125 (21.7)  
 Not insured 6 (0.2) 5 (0.2) 1 (0.2)  
 Unknown 57 (1.5) 51 (1.8) 6 (1.0)  
 Missing 11 (0.3) 11 (0.3) 0 (0.0)  
Median income    0.454 
 Low 1,331 (34.5) 1,124 (34.1) 207 (36.6)  
 Median 1,239 (32.1) 1,068 (32.4) 171 (30.2)  
 High 1,288 (33.4) 1,100 (33.4) 188 (33.2)  
Less than 12 years education    0.060 
 Low percentage 1,231 (31.9) 1,068 (32.4) 163 (28.8)  
 Middle percentage 1,270 (32.9) 1,090 (33.1) 180 (31.8)  
 High percentage 1,357 (35.2) 1,134 (34.5) 223 (39.4)  
Urban/rural recode    0.930 
 Big Metro 2,361 (60.5) 2,020 (60.7) 341 (59.3)  
 Metro 980 (25.1) 828 (24.9) 152 (26.4)  
 Urban 168 (4.3) 142 (4.3) 26 (4.5)  
 Less urban 317 (8.1) 271 (8.2) 46 (8.0)  
 Rural 76 (2.0) 66 (2.0) 10 (1.7)  
Grade    0.689 
 Grade I 196 (5.0) 162 (4.9) 34 (5.9)  
 Grade II 2,383 (61.1) 2,046 (61.5) 337 (58.6)  
 Grade III 1,110 (28.4) 938 (28.2) 172 (29.9)  
 Grade IV 119 (3.1) 101 (3.0) 18 (3.1)  
 Unknown 95 (2.4) 81 (2.4) 14 (2.4)  
CCI    <0.001 
 No comorbidity 1,608 (41.2) 1,443 (43.4) 165 (28.7)  
 1 956 (24.5) 814 (24.5) 142 (24.7)  
 2+ 1,337 (34.3) 1,069 (32.1) 268 (46.6)  
Chemotherapy    <0.001 
 No 2,523 (64.6) 2,078 (62.4) 445 (77.4)  
 Yes 1,380 (35.4) 1,250 (37.6) 130 (22.6)  

Cancer-specific survival for patients with preexisting dementia was significantly worse than for their cognitively healthy counterparts regardless of the algorithms used for dementia identification (shown in Table 2). Being younger (65–84 years old) was associated with better cancer-specific survival. Patients residing in areas with residents attaining higher levels of education had better survival outcomes, whereas median income showed no significant effect. The risk of cancer-related death increased significantly as tumor grade advanced. Receipt of chemotherapy was significantly associated with better cancer-specific survival.

Table 2.

Effect of preexisting dementia on cancer-specific survival for patients with stage III colon cancer based on Cox proportional hazards models

HR (95% CI)
VariablesModel 1Model 2
Presence of preexisting dementia 
 No dementia Reference Reference 
 Dementia (any evidence) 1.45 (1.29–1.63)a — 
 Dementia (both diagnosis and prescription) — 1.23 (0.99–1.52)b 
 Dementia (diagnosis only)  1.59 (1.35–1.87)b 
 Dementia (prescription only)  1.93 (1.14–3.28)b 
Age 
 65–84 0.59 (0.53–0.66) 0.58 (0.52–0.65) 
 84+ Reference Reference 
Gender 
 Male 1.00 (0.91–1.10) 1.00 (0.91–1.09) 
 Female Reference Reference 
Race 
 White Reference Reference 
 Black 0.94 (0.80–1.10) 0.93 (0.79–1.09) 
 Hispanic 0.88 (0.62–1.25) 0.86 (0.61–1.23) 
 Asian 0.7t6 (0.59–0.96) 0.75 (0.59–0.95) 
Marital status 
 Married 0.94 (0.80–1.10) 0.94 (0.80–1.11) 
 Single Reference Reference 
Insurance types 
 Insured, NOS 0.70 (0.48–1.02) 0.69 (0.47–1.01) 
 Medicaid/low income 1.51 (0.98–2.32) 1.49 (0.97–2.29) 
 Medicare 1.14 (1.03–1.26) 1.15 (1.04–1.27) 
 Private/government Reference Reference 
 Not insured 0.94 (0.35–2.53) 0.94 (0.35–2.52) 
Median income 
 Low Reference Reference 
 Median 1.03 (0.91–1.16) 1.02 (0.91–1.15) 
 High 1.07 (0.93–1.24) 1.08 (0.93–1.24) 
Less than 12 years education 
 Low percentage 0.78 (0.67–0.90) 0.78 (0.68–0.91) 
 Middle percentage 0.93 (0.83–1.05) 0.94 (0.83–1.06) 
 High percentage Reference Reference 
Grade 
 Grade I Reference Reference 
 Grade II 1.10 (0.87–1.39) 1.10 (0.88–1.39) 
 Grade III 2.08 (1.65–2.63) 2.10 (1.66–2.65) 
 Grade IV 2.57 (1.91–3.48) 2.56 (1.90–3.46) 
 Unknown 2.39 (1.74–3.29) 2.43 (1.76–3.34) 
CCI 
 No comorbidity 1.00 (0.90–1.11) 0.99 (0.89–1.10) 
 1 1.01 (0.90–1.13) 1.00 (0.89–1.13) 
 2+ Reference Reference 
Chemotherapy 
 No Reference Reference 
 Yes 0.56 (0.50–0.61) 0.55 (0.50–0.61) 
HR (95% CI)
VariablesModel 1Model 2
Presence of preexisting dementia 
 No dementia Reference Reference 
 Dementia (any evidence) 1.45 (1.29–1.63)a — 
 Dementia (both diagnosis and prescription) — 1.23 (0.99–1.52)b 
 Dementia (diagnosis only)  1.59 (1.35–1.87)b 
 Dementia (prescription only)  1.93 (1.14–3.28)b 
Age 
 65–84 0.59 (0.53–0.66) 0.58 (0.52–0.65) 
 84+ Reference Reference 
Gender 
 Male 1.00 (0.91–1.10) 1.00 (0.91–1.09) 
 Female Reference Reference 
Race 
 White Reference Reference 
 Black 0.94 (0.80–1.10) 0.93 (0.79–1.09) 
 Hispanic 0.88 (0.62–1.25) 0.86 (0.61–1.23) 
 Asian 0.7t6 (0.59–0.96) 0.75 (0.59–0.95) 
Marital status 
 Married 0.94 (0.80–1.10) 0.94 (0.80–1.11) 
 Single Reference Reference 
Insurance types 
 Insured, NOS 0.70 (0.48–1.02) 0.69 (0.47–1.01) 
 Medicaid/low income 1.51 (0.98–2.32) 1.49 (0.97–2.29) 
 Medicare 1.14 (1.03–1.26) 1.15 (1.04–1.27) 
 Private/government Reference Reference 
 Not insured 0.94 (0.35–2.53) 0.94 (0.35–2.52) 
Median income 
 Low Reference Reference 
 Median 1.03 (0.91–1.16) 1.02 (0.91–1.15) 
 High 1.07 (0.93–1.24) 1.08 (0.93–1.24) 
Less than 12 years education 
 Low percentage 0.78 (0.67–0.90) 0.78 (0.68–0.91) 
 Middle percentage 0.93 (0.83–1.05) 0.94 (0.83–1.06) 
 High percentage Reference Reference 
Grade 
 Grade I Reference Reference 
 Grade II 1.10 (0.87–1.39) 1.10 (0.88–1.39) 
 Grade III 2.08 (1.65–2.63) 2.10 (1.66–2.65) 
 Grade IV 2.57 (1.91–3.48) 2.56 (1.90–3.46) 
 Unknown 2.39 (1.74–3.29) 2.43 (1.76–3.34) 
CCI 
 No comorbidity 1.00 (0.90–1.11) 0.99 (0.89–1.10) 
 1 1.01 (0.90–1.13) 1.00 (0.89–1.13) 
 2+ Reference Reference 
Chemotherapy 
 No Reference Reference 
 Yes 0.56 (0.50–0.61) 0.55 (0.50–0.61) 

aThe overall effect of preexisting dementia on survival.

bThe effect of source of evidence of preexisting dementia on survival.

The mediating effect analysis used AFT models, with dementia identified through either a formal diagnosis or a drug prescription. For patients who received no chemotherapy, the average mean survival time for those with preexisting dementia was 63% that of patients with no preexisting dementia. The odds of receiving chemotherapy were reduced by 9% for patients with preexisting dementia compared with patients with no dementia (as shown in Table 3).

Table 3.

Mediation analysis with causal effects estimated for presence of dementia at the mean level of the covariates, based on AFT models

NDEa (95% CI)NIEb (95% CI)
Preexisting dementia 0.63 (0.55–0.72) 0.91 (0.88–0.94) 
Coexisting dementia 0.76 (0.67–0.85) 0.93 (0.91–0.95) 
NDEa (95% CI)NIEb (95% CI)
Preexisting dementia 0.63 (0.55–0.72) 0.91 (0.88–0.94) 
Coexisting dementia 0.76 (0.67–0.85) 0.93 (0.91–0.95) 

aNDE: estimated effect on the mean survival time of a person simply having dementia but treated just like a person without dementia, compared with a person without dementia. It captures decrease in survival due to having dementia.

bNIE: estimated impact on effect on the mean survival time of current chemotherapy practice for people with dementia, compared with the hypothetical situation where a person with dementia is as likely to get chemotherapy as a person without dementia. It captures the decrease in survival time due to someone with dementia potentially receiving more aggressive treatment.

The average mean survival time of stage III colon cancer patients with the presence of preexisting dementia is 57% that of patients with no evidence of dementia. Chemotherapy was a statistically significant mediator for the presence of dementia on survival for stage III colon cancer patients. The effect of presence of dementia was mediated by receipt of chemotherapy by 13% for preexisting dementia (shown in Table 4).

Table 4.

Proportion of effect of presence of dementia mediated by receipt of chemotherapy

Total effecta (95% CI)Proportion mediated
Preexisting dementia 0.57 (0.50–0.66) 13% 
Coexisting dementia 0.70 (0.62–0.79) 18% 
Total effecta (95% CI)Proportion mediated
Preexisting dementia 0.57 (0.50–0.66) 13% 
Coexisting dementia 0.70 (0.62–0.79) 18% 

aTotal effect is the product of NDE and NIE; combined effect on survival time of having dementia, then potentially having more aggressive treatment.

In secondary analyses, we examined the impact of expanding the definition of dementia to include coexisting dementia, diagnosed at or after the diagnosis of cancer. Overall, the impact of a coexisting dementia diagnosis on cancer survival was less than that for preexisting dementia. Mean survival was reduced by 70% for coexisting dementia compared with patients with no evidence of dementia; receipt of chemotherapy mediated this effect on survival by 18%.

The main findings of this study can be summarized in two points. First, the presence of a preexisting diagnosis of dementia, identified by either medical history or medication history-based algorithms, was significantly associated with worse cancer-specific survival for patients with stage III colon cancer. Second, the receipt of chemotherapy was a significant mediator on the causal pathway of presence of dementia on survival outcome for stage III colon cancer patients. In other words, nearly 20% of the worse survival in patients with dementia and stage III colon cancer could be explained by the decreased odds of receiving chemotherapy.

Consistent with another study, we found that patients with dementia had significantly worse survival than their cognitively healthy counterparts, even after adjusting for the receipt of cancer treatment (15). Two possible explanations have been proposed: The physician may elect not to recommend chemotherapy, and even if it is recommended, the patient and family may decline to pursue this option. From a physician's perspective, depending on the specific degree and nature of the cognitive impairment, a variety of behavior issues may arise to complicate informed decision making and consent for these cancer patients with dementia. Disorganized thinking may also hinder a person's ability to follow medical recommendations, such as scheduling follow-up medical appointments or adhering to complex treatment regimens (23). A further consideration for dementia patients is higher risk of chemotherapy-related toxicities (24), especially those that might worsen cognitive impairment. Even if patients with dementia were prescribed a typical postsurgical chemotherapy, the course might be less aggressive to ensure the completion (6). Thus, physicians may hesitate to recommend chemotherapy, including enrollment in clinical trials, for patients with dementia (23, 25, 26).

Second, individuals with a preexisting dementia and their families must also weigh risks and benefits, even if they are informed about potential survival benefits of chemotherapy. Adherence to cancer care guidelines generated from populations with normal cognition may yield limited survival benefits for older patients with more advanced dementia (15). Indeed, use of less invasive diagnostic and staging procedures in patients with cancer and dementia may reflect good clinical judgment on the part of caregivers and clinicians (13). Older cancer patients or their families are more likely to choose less invasive therapies or to forgo treatment if the patient has dementia or functional limitations or if life expectancy is perceived to be brief (27). In particular, cancer patients diagnosed at later stages are among the most likely to refuse treatment (28). Some patients and families, however, may still consider potentially curative cancer chemotherapy worthwhile. This is especially likely for patients with early-stage dementia, because median survival without chemotherapy is about 24 months (29), while survival after initial dementia diagnosis may be as long as 4 to 8 years (30).

There are two limitations of this study. The primary limitation is that the SEER-Medicare database does not include detailed information on the dementia diagnosis or functional status, so that we were not able to identify the extent of the dementia. A second limitation is that we do not know whether the choice of not using chemotherapy represented physician advice, or patient/family choice, and what other grounds either might have had for deciding against chemotherapy. It is possible that patients with dementia receive less screening, either due to diminished recommendation or diminished capacity to undergo screening. If this were the case, colon cancer would be diagnosed only when symptomatic and would on average be a more advanced/poorer prognosis case than those found incidentally on screening. Therefore, less aggressive cancer treatment is more likely to be a patient/family choice, because it would not be recommended by a physician to maintain patient's overall quality of life.

Approaches to mediation analysis with uncorrelated survival data include Cox proportional hazards and AFT models. The primary strength of this article is that we employed AFT model and combined with the counterfactual approach for a rigorous causal interpretation for the mediation effect, while the Cox proportional hazards model can only provide a valid test for the presence of a mediator effect according to the product–coefficient method (15).

Adjuvant chemotherapy is a standard component of treatment for patients diagnosed with stage III colon cancer. Previous studies have shown that chemotherapy can have a deleterious effect on cognitive function (31, 32). Despite several research studies about the effect of dementia on cancer treatment and survival, the impact of diminished chemotherapy as a causative factor in these reduced survival outcomes was not previously known. Patients at a high risk for cognitive impairment have often been excluded from existing studies of cancer (33). In the current study, we provide the first estimate of the mediating effect of diminished chemotherapy in patients with stage III colon cancer and dementia, simultaneously demonstrating the cancer-specific survival benefit of chemotherapy in the presence of dementia. In this study, we were unable to determine the exact chemotherapy regimen delivered to patients. Nonetheless, diminished receipt of any adjuvant chemotherapy was found to account for 18% of the diminished survival of stage III colon cancer patients with dementia. Currently, there is limited evidence showing that chemotherapy is associated with a measurable deterioration of cognitive function for cancer patients (9, 34). However, whether this effect is greater with certain chemotherapy drugs or in patients with preexisting dementia is unknown. Future studies should assess the effect of adjuvant chemotherapy on cognitive function in patients with preexisting dementia and determine whether interventions that enhance the provision of standard adjuvant chemotherapy enhance the survival of patients with concomitant stage III colon cancer and dementia.

D.J. Tancredi is a consultant/advisory board member for Pfizer Consumer Health. No potential conflicts of interest were disclosed by the other authors.

Conception and design: Y. Chen, R.D. Cress, L. Beckett

Development of methodology: Y. Chen, S.L. Stewart

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): Y. Chen, R.D. Cress

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Y. Chen, S.L. Stewart, T.J. Semrad, D. Harvey, D.J. Tencredi, L. Beckett

Writing, review, and/or revision of the manuscript: Y. Chen, R.D. Cress, S.L. Stewart, T.J. Semrad, D. Harvey, D.J. Tencredi, L. Beckett

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Y. Chen

Study supervision: R.D. Cress, L. Beckett

1.
Siegel
RL
,
Miller
KD
,
Jemal
A
. 
Cancer statistics, 2016
.
CA Cancer J Clin
2016
;
66
:
7
30
.
2.
Wortmann
M
. 
Dementia: a global health priority - highlights from an ADI and World Health Organization report
.
Alzheimers Res Ther
2012
;
4
:
40
.
3.
Siegel
RL
,
Miller
KD
,
Fedewa
SA
,
Ahnen
DJ
,
Meester
RGS
,
Barzi
A
, et al
Colorectal cancer statistics, 2017
.
CA Cancer J Clin
2017
;
67
:
177
93
.
4.
Wolmark
N
,
Rockette
H
,
Mamounas
E
,
Jones
J
,
Wieand
S
,
Wickerham
DL
, et al
Clinical trial to assess the relative efficacy of fluorouracil and leucovorin, fluorouracil and levamisole, and fluorouracil, leucovorin, and levamisole in patients with Dukes' B and C carcinoma of the colon: results from National Surgical Adjuvant Breast and Bowel Project C-04
.
J Clin Oncol
1999
;
17
:
3553
9
.
5.
Andre
T
,
Boni
C
,
Mounedji-Boudiaf
L
,
Navarro
M
,
Tabernero
J
,
Hickish
T
, et al
Oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment for colon cancer
.
N Engl J Med
2004
;
350
:
2343
51
.
6.
Sanoff
HK
,
Carpenter
WR
,
Sturmer
T
,
Goldberg
RM
,
Martin
CF
,
Fine
JP
, et al
Effect of adjuvant chemotherapy on survival of patients with stage III colon cancer diagnosed after age 75 years
.
J Clin Oncol
2012
;
30
:
2624
34
.
7.
NIH
. 
Adjuvant therapy for patients with colon and rectal cancer
.
Conn Med
1990
;
54
:
573
81
.
8.
Lilienfeld
DE
,
Perl
DP
. 
Projected neurodegenerative disease mortality in the United States, 1990-2040
.
Neuroepidemiology
1993
;
12
:
219
28
.
9.
Extermann
M
,
Aapro
M
. 
Assessment of the older cancer patient
.
Hematol Oncol Clin North Am
2000
;
14
:
63
77
,
viii
ix
.
10.
Robb
C
,
Boulware
D
,
Overcash
J
,
Extermann
M
. 
Patterns of care and survival in cancer patients with cognitive impairment
.
Crit Rev Oncol Hematol
2010
;
74
:
218
24
.
11.
Mohammadi
M
,
Cao
Y
,
Glimelius
I
,
Bottai
M
,
Eloranta
S
,
Smedby
KE
. 
The impact of comorbid disease history on all-cause and cancer-specific mortality in myeloid leukemia and myeloma - a Swedish population-based study
.
BMC Cancer
2015
;
15
:
850
.
12.
Baillargeon
J
,
Kuo
YF
,
Lin
YL
,
Raji
MA
,
Singh
A
,
Goodwin
JS
. 
Effect of mental disorders on diagnosis, treatment, and survival of older adults with colon cancer
.
J Am Geriatr Soc
2011
;
59
:
1268
73
.
13.
Gupta
SK
,
Lamont
EB
. 
Patterns of presentation, diagnosis, and treatment in older patients with colon cancer and comorbid dementia
.
J Am Geriatr Soc
2004
;
52
:
1681
7
.
14.
Islam
KM
,
Jiang
X
,
Anggondowati
T
,
Lin
G
,
Ganti
AK
. 
Comorbidity and survival in lung cancer patients
.
Cancer Epidemiol Biomarkers Prev
2015
;
24
:
1079
85
.
15.
Raji
MA
,
Kuo
YF
,
Freeman
JL
,
Goodwin
JS
. 
Effect of a dementia diagnosis on survival of older patients after a diagnosis of breast, colon, or prostate cancer: implications for cancer care
.
Arch Intern Med
2008
;
168
:
2033
40
.
16.
Warren
JL
,
Klabunde
CN
,
Schrag
D
,
Bach
PB
,
Riley
GF
. 
Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population
.
Med Care
2002
;
40
:
IV-3
18
.
17.
Quan
H
,
Sundararajan
V
,
Halfon
P
,
Fong
A
,
Burnand
B
,
Luthi
JC
, et al
Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data
.
Med Care
2005
;
43
:
1130
9
.
18.
Charlson
ME
,
Pompei
P
,
Ales
KL
,
MacKenzie
CR
. 
A new method of classifying prognostic comorbidity in longitudinal studies: development and validation
.
J Chronic Dis
1987
;
40
:
373
83
.
19.
Klabunde
CN
,
Warren
JL
,
Legler
JM
. 
Assessing comorbidity using claims data: an overview
.
Med Care
2002
;
40
:
IV-26
35
.
20.
VanderWeele
TJ
. 
Causal mediation analysis with survival data
.
Epidemiology
2011
;
22
:
582
5
.
21.
Vanderweele
TJ
,
Vansteelandt
S
. 
Odds ratios for mediation analysis for a dichotomous outcome
.
Am J Epidemiol
2010
;
172
:
1339
48
.
22.
Valeri
L
,
VanderWeele
TJ
. 
SAS macro for causal mediation analysis with survival data
.
Epidemiology
2015
;
26
:
e23
4
.
23.
Frayne
SM
,
Halanych
JH
,
Miller
DR
,
Wang
F
,
Lin
H
,
Pogach
L
, et al
Disparities in diabetes care: impact of mental illness
.
Arch Intern Med
2005
;
165
:
2631
8
.
24.
Verstappen
CC
,
Heimans
JJ
,
Hoekman
K
,
Postma
TJ
. 
Neurotoxic complications of chemotherapy in patients with cancer: clinical signs and optimal management
.
Drugs
2003
;
63
:
1549
63
.
25.
Monfardini
S
,
Ferrucci
L
,
Fratino
L
,
del Lungo
I
,
Serraino
D
,
Zagonel
V
. 
Validation of a multidimensional evaluation scale for use in elderly cancer patients
.
Cancer
1996
;
77
:
395
401
.
26.
Vardy
J
,
Rourke
S
,
Tannock
IF
. 
Evaluation of cognitive function associated with chemotherapy: a review of published studies and recommendations for future research
.
J Clin Oncol
2007
;
25
:
2455
63
.
27.
Hurria
A
,
Leung
D
,
Trainor
K
,
Borgen
P
,
Norton
L
,
Hudis
C
. 
Factors influencing treatment patterns of breast cancer patients age 75 and older
.
Crit Rev Oncol Hematol
2003
;
46
:
121
6
.
28.
Bland
KI
,
Menck
HR
,
Scott-Conner
CE
,
Morrow
M
,
Winchester
DJ
,
Winchester
DP
. 
The national cancer data base 10-year survey of breast carcinoma treatment at hospitals in the United States
.
Cancer
1998
;
83
:
1262
73
.
29.
Stathopoulos
GP
. 
Survival of untreated advanced colorectal cancer patients
.
Oncol Lett
2011
;
2
:
731
3
.
30.
Xie
J
,
Brayne
C
,
Matthews
FE
,
Medical Research Council Cognitive Function and Ageing Study collaborators
. 
Survival times in people with dementia: analysis from population based cohort study with 14 year follow-up
.
BMJ
2008
;
336
:
258
62
.
31.
Ferguson
RJ
,
Ahles
TA
. 
Low neuropsychologic performance among adult cancer survivors treated with chemotherapy
.
Curr Neurol Neurosci Rep
2003
;
3
:
215
22
.
32.
Minisini
A
,
Atalay
G
,
Bottomley
A
,
Puglisi
F
,
Piccart
M
,
Biganzoli
L
. 
What is the effect of systemic anticancer treatment on cognitive function?
Lancet Oncol
2004
;
5
:
273
82
.
33.
Rodin
G
,
Ahles
TA
. 
Accumulating evidence for the effect of chemotherapy on cognition
.
J Clin Oncol
2012
;
30
:
3568
9
.
34.
Chen
H
,
Cantor
A
,
Meyer
J
,
Beth Corcoran
M
,
Grendys
E
,
Cavanaugh
D
, et al
Can older cancer patients tolerate chemotherapy? A prospective pilot study
.
Cancer
2003
;
97
:
1107
14
.