Abstract
Background:
Preclinical evidence suggests a link between the renin-angiotensin system and oncogenesis. We aimed to explore the impact of angiotensin-converting enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARB) in head and neck cancer (HNC).
Methods:
Over 5,000 patients were identified from the Surveillance, Epidemiology, and End Results-Medicare linked dataset and categorized according to ACEi and ARB and diagnoses of chronic kidney disease (CKD) or hypertension (HTN). Overall survival (OS) and cancer-specific survival (CSS) were compared using Cox multivariable regression (MVA), expressed as hazard ratios (HR) with 95% confidence intervals (95%CI).
Results:
No significant MVA associations for OS or CSS were found for ACEi. Compared to patients with CKD/HTN taking ARB, those with CKD/HTN not taking ARB experienced worse OS (HR 1.28, 95%CI 1.09–1.51, p=0.003) and CSS (HR 1.23, 95% 1.00–1.50, p=0.050).
Conclusions:
ARB usage is associated with improved OS and CSS among HNC patients with CKD or HTN.
Keywords: angiotensin converting enzyme inhibitor, angiotensin II receptor blocker, renin-angiotensin-aldosterone system, head and neck cancer, SEER-Medicare
Introduction:
The American Cancer Society estimates that head and neck cancer (HNC) will afflict more than 66,000 individuals in the United States (US) and claim the lives of over 14,000 this year1. Across the globe, there are more than 887,000 annual cases and over 453,000 deaths attributed to HNC according to the most recent report of the International Agency for Research on Cancer2. Despite the favorable outcomes among the growing portion of patients with human papillomavirus (HPV)-driven HNC, outcomes remain suboptimal among patients with non-HPV-associated HNC, with three year rates of survival failing to exceed 65%3,4. This highlights the unmet need for novel therapeutic approaches in HNC.
Preclinical data have implicated dysregulation of the renin-angiotensin system (RAS) in stimulating angiogenesis, proliferation, and growth in HNC5. In-vitro and in vivo studies have demonstrated RAS inhibition can inhibit these oncogenic processes6–8. These findings raise the intriguing possibility of augmenting HNC therapy by incorporating agents that target the RAS, such as angiotensin-converting enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARB).
Although RAS inhibitors offer the advantages of prior approval by the United States Food and Drug Administration, established safety and pharmacodynamic profiles, widespread availability across the globe, and low cost, clinical evidence supporting the use of these medications in HNC is limited. One study evaluating multiple classes of antihypertensive agents in 1,274 Korean patients treated definitively for HNC demonstrated no advantages in disease-free survival, overall survival, cancer-specific survival, or non-cancer survival among the 71 individuals receiving ACEi/ARB9. In contrast, a larger and more recent study from Taiwan analyzed 927 patients with nasopharyngeal carcinoma, 272 of whom received ARB, and identified improvements in overall and cancer-specific survival in exposed patients8. While these studies together included thousands of patients, only a few hundred were taking RAS inhibitors, and they each focused on a single institution, limiting the generalizability of their findings. Here, we aimed to evaluate the survival impact of ACEi and ARB therapy in a larger, nationwide cohort of HNC patients by evaluating recent outcomes from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked dataset.
Materials and Methods:
Data Source
The linked SEER-Medicare dataset combines two data sources. SEER uses population-based cancer registries to aggregate data on cancer cases occurring in approximately 35% of the US population, including demographics, tumor characteristics, treatment, census-tract level socioeconomic metrics, mortality, and cause of death. Medicare claims provide data on diagnoses and prescription medications. Diagnoses are reported using the International Classification of Diseases, Ninth Revision (ICD-9), Clinical Modification codes, Current Procedural Terminology (CPT) codes, and Healthcare Common Procedure Coding System (HCPCS). In 2006, Medicare initiated the optional Part D drug benefit, which covers outpatient prescription drugs to supplement traditional Medicare and Medicare Advantage plans. Part D claims are filed for each event in which a prescription is filled and include the date of service. This study was performed with the approval of the Colorado Multiple Institutional Review Board.
Sample Selection
From our initial cohort of cancers of the head and neck diagnosed through 2015, we selected patients whose first and only primary tumor was a non-metastatic squamous cell carcinoma (International Classification of Diseases for Oncology [ICD-O-3] morphology codes 8050–8089) of the head and neck (ICD-O-3 topography codes C00-C14) diagnosed from 2008 through 2015. We selected 2008 as the earliest year of diagnosis to ensure that at least one full year of Part D data was available prior to diagnosis (other than the initial year of the program), and 2015 was selected as the latest year of diagnosis to ensure most patients would have 24 months of follow-up. Patients with unknown diagnosis dates, negative survival time, or diagnoses identified by autopsy or death certificate were excluded. To capture patients with complete Medicare data, we included only beneficiaries who were at least 66 years old at diagnosis and continuously enrolled in fee-for-service Medicare Parts A, B, and D for both 12 months before and 12 months following the month of diagnosis (or until death if within 12 months of diagnosis). Finally, patients with no paid claims during the 12-month observation period were excluded to yield our analytic cohort of patients with complete claims data to examine prior health status, treatment, and outcomes of interest.
We used CPT, HCPCS, ICD-9, and NDC codes reported in the Medicare Provider Analysis and Review (MEDPAR), outpatient National Claims History Physician/Supplier, Durable Medical Equipment, and Part D (PDESAF) claims to identify patients undergoing definitive-intent therapy, which we defined as surgery, radiotherapy, or chemotherapy initiated within six months after diagnosis. Lastly, we excluded patients with unknown race, unknown census tract, unknown nodal stage, or nodal stage of “Not Applicable” (Figure 1).
Figure 1.
Cohort Derivation. HTN, hypertension; CKD, chronic kidney disease; ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker
Outcomes
The initial analysis examined characteristics associated with ACEi or ARB use and diseases for which these are typically prescribed. Our primary focus centered on ACEi/ARB use and common diagnoses for which these medications are prescribed; however, we also incorporated statin usage and dyslipidemia status as covariates in light of recent Danish10 and US data11, as well as metformin usage and comorbid diabetes12. Prescription drugs were identified using generic names, brand names, and NDC codes on PDSAF claims. Medication use was defined as having three or more prescriptions filled in the 12 months prior to diagnosis and three or more prescriptions filled in the year since diagnosis, unless a patient died less than a year from diagnosis, in which case we required at least one prescription filled for every four months of survival. The associated chronic conditions were identified using the ICD-9 diagnosis codes used in the Chronic Conditions Data Warehouse algorithms. We considered a patient with at least one diagnosis reported on a MEDPAR, outpatient, or NCH claim in the year prior to diagnosis to have the condition.
The primary outcome of interest was two-year OS, measured as the number of months from diagnosis until death due to any cause, with patients surviving more than two years censored after 24 months. As Medicare-reported death data are more robust than those reported in SEER, we used the former to assess OS through 2011. However, only SEER captures data regarding cancer-specific survival (CSS). For this outcome, patients dying of causes other than cancer were censored at the time of death.
Exposure
As RAS-inhibiting therapies are typically prescribed to patients with hypertension (HTN) or chronic kidney disease (CKD), we classified patients with respect to these diseases and ACEi usage into categories: (1) negative for HTN or CKD and negative for ACEi, i.e. nD; (2) positive for HTN or CKD and negative for ACEi, i.e. DnACEi; and (3) positive for HTN or CKD and positive for ACEi, i.e. D+ACEi. Patients were classified into three analogous groups with respect to ARB: (1) nD; (2) DnARB; (3) D+ARB.
Control Variables
In all multivariable analyses, we adjusted for patient gender, age, race, marital status, SEER registry, population density (metropolitan, urban, and rural), census tract percentage of population with high school education only, census tract percentage of population below poverty, primary tumor site, and AJCC T- and N- classifications. Using Medicare claims, we also identified and controlled for whether the primary treatment facility was a teaching hospital. To address potential differences in overall health, Medicare claims from the year prior to diagnosis were used to calculate Charlson Comorbidity Index (CCI) values according to the National Cancer Institute adaptation of the algorithm13. Prognostic factors for HNC including HPV status, alcohol abuse, and tobacco abuse are not available in SEER.
Statistical Analysis
All statistical analyses were performed using SPSS (SPSS Inc., Chicago, IL). Pearson chi-square tests were used to assess univariable associations between categorical variables and disease/medication categories. For each drug class, OS and CSS were first examined using the Kaplan-Meier (KM) method. Next, univariable Cox regression was performed to generate unadjusted models for survival, expressed as hazard ratios (HR) with corresponding 95% confidence intervals (95%CI), with HR>1 indicating greater risk for mortality. Then, multivariable Cox regression analysis was performed to generate adjusted models for survival, evaluated at a significance level of p<0.050. The proportional hazards assumption was assessed using a test of Schoenfeld residuals for covariates in all final models and returned no significant results14. In addition, visual inspection of the Kaplan-Meier curves demonstrated parallel trajectories between groups, further supporting the proportional hazards assumption for the analysis.
Given the heterogeneity of patients included in the analysis, subgroup analysis was conducted among populations of interest, namely T-classification, N-classification, primary site, facility type, surgery receipt, chemotherapy receipt, and radiotherapy receipt. Sixteen distinct subgroups were analyzed, and multivariable Cox regression analysis was performed within each to generate adjusted models for OS and CSS. To account for multiple testing, significance was evaluated at a corrected significance level of p<0.003.
Results:
Descriptive Statistics
Baseline sociodemographic, cancer-specific, clinical, treatment, and medication-related characteristics of our study population are depicted in Supplemental Tables 1 and 2. For the ACEi model, 5,075 patients were identified, of whom 1,247 were classified as taking ACEi. The ARB model contained 5,120 subjects, with 687 taking ARB.
There were significant differences across disease/medication groups in most of these factors. Notably, ACEi patients were more likely to be white and to reside in non-metropolitan areas in the Midwest or South and in census tracts with lower educational attainment and greater poverty. They were also more likely to have cancers arising from the lip and localized cancers. ARB patients were more likely to be older than 69 years of age, female, married or partnered, and to reside in metropolitan areas outside of the Midwest and in census tracts with greater educational attainment. They were more likely to have T0–1 and N0 disease and tumors arising from the oral cavity. They were also more likely to receive care at an NCI center and to undergo surgery. Patients taking either ACEi or ARB were each more likely to have a higher comorbidity burden, including diabetes mellitus and dyslipidemia, and to be taking statin, fibrate, and metformin therapy.
Kaplan-Meier, univariable Cox regression, and multivariable Cox regression models for OS are presented in Table 1 (ACEi) and Table 2 (ARB), and corresponding models for CSS are depicted in Table 3 (ACEi) and Table 4 (ARB).
Table 1.
Overall Survival, ACEi cohort
| Kaplan-Meier | Cox Univariable Analysis | Cox Multivariable Analysis | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| OS2 (%) | 95%CI (%) | p (logrank) | HR | 95%CI | p (class) | HR | 95%CI | p (class) | p (variable) | |
| Disease/Drug Category | 68.7 | 66.0–71.2 | <0.001 | - | - | - | - | 0.065 | ||
| 63.5 | 61.6–65.2 | 1.23 | 1.09–1.38 | <0.001 | 1.12 | 0.99–1.27 | 0.067 | |||
| 69.4 | 66.4–72.1 | 0.98 | 0.84–1.13 | 0.742 | 0.98 | 0.82–1.16 | 0.796 | |||
| Age | 73.0 | 71.3–74.6 | <0.001 | - | - | - | - | - | - | <0.001 |
| 62.0 | 59.6–64.3 | 1.52 | 1.37–1.70 | <0.001 | 1.62 | 1.45–1.81 | <0.001 | |||
| 46.5 | 42.6–50.3 | 2.46 | 2.16–2.80 | <0.001 | 2.48 | 2.15–2.87 | <0.001 | |||
| Sex | 67.5 | 65.8–69.0 | <0.001 | - | - | - | - | - | 0.888 | |
| 63.0 | 60.6–65.2 | 1.19 | 1.08–1.31 | <0.001 | 1.01 | 0.90–1.13 | 0.888 | |||
| Race | 67.2 | 65.7–68.6 | <0.001 | - | - | - | - | - | - | 0.429 |
| 60.7 | 57.5–63.7 | 1.24 | 1.11–1.39 | <0.001 | 1.05 | 0.93–1.19 | 0.429 | |||
| Marital Status | 72.6 | 70.8–74.4 | <0.001 | - | - | - | - | - | - | <0.001 |
| 59.6 | 57.7–61.5 | 1.64 | 1.48–1.81 | <0.001 | 1.33 | 1.20–1.48 | <0.001 | |||
| Geographic Region | 66.9 | 64.8–68.9 | <0.001 | - | - | - | - | - | - | 0.283 |
| 68.0 | 64.9–70.9 | 0.97 | 0.85–1.11 | 0.651 | 0.93 | 0.80–1.09 | 0.386 | |||
| 66.5 | 62.6–70.1 | 1.02 | 0.88–1.20 | 0.770 | 1.07 | 0.90–1.27 | 0.440 | |||
| 63.0 | 60.4–65.4 | 1.18 | 1.05–1.32 | 0.005 | 1.08 | 0.94–1.23 | 0.266 | |||
| Population Density | 66.0 | 64.5–67.5 | 0.654 | - | - | - | - | - | - | 0.866 |
| 65.3 | 62.0–68.3 | 1.03 | 0.91–1.17 | 0.603 | 0.91 | 0.65–1.28 | 0.599 | |||
| 68.8 | 56.6–76.4 | 0.89 | 0.64–1.23 | 0.478 | 0.99 | 0.86–1.13 | 0.841 | |||
| Year of Diagnosis | 63.4 | 58.9–67.3 | 0.040 | - | - | - | - | - | - | 0.016 |
| 63.8 | 59.6–67.8 | 0.97 | 0.79–1.19 | 0.773 | 0.97 | 0.79–1.18 | 0.730 | |||
| 61.6 | 57.4–65.6 | 1.05 | 0.56–1.27 | 0.653 | 1.02 | 0.83–1.24 | 0.869 | |||
| 66.8 | 62.9–70.4 | 0.88 | 0.72–1.08 | 0.216 | 0.81 | 0.66–0.99 | 0.040 | |||
| 66.7 | 62.9–70.2 | 0.88 | 0.73–1.08 | 0.217 | 0.86 | 0.71–1.05 | 0.132 | |||
| 68.0 | 64.4–71.3 | 0.83 | 0.68–1.01 | 0.060 | 0.87 | 0.72–1.06 | 0.169 | |||
| 69.9 | 66.6–72.9 | 0.78 | 0.65–0.95 | 0.012 | 0.74 | 0.61–0.90 | 0.003 | |||
| 56.3 | 50.1–62.1 | 0.92 | 0.76–1.12 | 0.413 | 0.91 | 0.74–1.11 | 0.332 | |||
| Primary Site | 64.1 | 61.3–66.7 | <0.001 | - | - | - | - | - | - | <0.001 |
| 81.9 | 76.8–86.0 | 0.44 | 0.33–0.59 | <0.001 | 0.52 | 0.38–0.71 | <0.001 | |||
| 58.5 | 50.3–65.7 | 1.13 | 0.87–1.46 | 0.365 | 0.76 | 0.58–0.99 | 0.039 | |||
| 66.9 | 64.2–69.4 | 0.92 | 0.80–1.05 | 0.221 | 0.62 | 0.53–0.74 | <0.001 | |||
| 65.2 | 54.1–74.3 | 1.01 | 0.70–1.46 | 0.968 | 0.71 | 0.48–1.05 | 0.087 | |||
| 45.3 | 38.6–51.7 | 1.74 | 1.42–2.13 | <0.001 | 0.97 | 0.77–1.21 | 0.781 | |||
| 68.6 | 66.1–70.9 | 0.85 | 0.75–0.97 | 0.015 | 0.76 | 0.65–0.89 | 0.001 | |||
| 62.0 | 56.3–67.2 | 1.08 | 0.88–1.33 | 0.451 | 1.01 | 0.82–1.24 | 0.947 | |||
| T-Classification | 82.8 | 80.9–84.6 | <0.001 | - | - | - | - | - | - | <0.001 |
| 64.9 | 62.3–67.3 | 2.27 | 1.96–2.62 | <0.001 | 1.76 | 1.27–2.44 | 0.001 | |||
| 52.1 | 48.3–55.8 | 3.51 | 3.00–4.11 | <0.001 | 3.45 | 2.44–4.89 | <0.001 | |||
| 43.7 | 40.1–47.2 | 4.47 | 3.85–5.19 | <0.001 | 4.16 | 2.99–5.78 | <0.001 | |||
| 64.6 | 59.7–69.0 | 2.38 | 1.95–2.91 | <0.001 | 2.78 | 1.82–4.23 | <0.001 | |||
| N-Classification | 73.9 | 72.2–75.4 | <0.001 | - | - | - | - | - | <0.001 | |
| 54.8 | 50.9–58.5 | 1.99 | 1.74–2.27 | <0.001 | 1.83 | 1.58–2.12 | <0.001 | |||
| 54.4 | 51.5–57.1 | 2.02 | 1.81–2.25 | <0.001 | 2.10 | 1.84–2.41 | <0.001 | |||
| 48.3 | 37.8–58.0 | 2.50 | 1.86–3.34 | <0.001 | 2.59 | 1.90–3.53 | <0.001 | |||
| Comorbidity Index | 73.8 | 71.7–75.7 | <0.001 | - | - | - | - | - | <0.001 | |
| 68.5 | 65.9–70.9 | 1.24 | 1.09–1.41 | 0.001 | 1.31 | 1.14–1.51 | <0.001 | |||
| 55.0 | 52.5–57.4 | 1.97 | 1.76–2.21 | <0.001 | 2.01 | 1.75–2.30 | <0.001 | |||
| 58.9 | 48.8–67.7 | 1.77 | 1.29–2.41 | <0.001 | 1.06 | 0.76–1.48 | 0.735 | |||
| Facility Type | 63.3 | 61.2–65.3 | <0.001 | - | - | - | - | - | <0.001 | |
| 72.7 | 69.2–75.9 | 0.69 | 0.59–0.81 | <0.001 | 0.70 | 0.59–0.83 | <0.001 | |||
| 66.5 | 64.4–68.4 | 0.90 | 0.82–1.00 | 0.051 | 0.90 | 0.80–1.00 | 0.044 | |||
| Tract % High School Only | 68.3 | 66.4–70.1 | <0.001 | - | - | - | - | - | 0.149 | |
| 63.7 | 61.7–65.5 | 1.19 | 1.08–1.31 | <0.001 | 1.09 | 0.97–1.23 | 0.149 | |||
| Tract % Below Poverty | 69.2 | 67.3–71.0 | <0.001 | - | - | - | - | - | 0.141 | |
| 62.8 | 60.8–64.6 | 1.26 | 1.15–1.39 | <0.001 | 1.09 | 0.97–1.22 | 0.141 | |||
| Surgery | 60.8 | 58.8–62.6 | <0.001 | - | - | - | - | - | <0.001 | |
| 71.7 | 69.8–73.5 | 0.66 | 0.60–0.73 | <0.001 | 0.62 | 0.54–0.71 | <0.001 | |||
| Chemotherapy | 71.1 | 69.4–72.7 | <0.001 | - | - | - | - | - | 0.517 | |
| 58.8 | 56.6–60.9 | 1.52 | 1.39–1.68 | <0.001 | 0.96 | 0.84–1.09 | 0.517 | |||
| Radiotherapy | 72.2 | 69.8–74.4 | <0.001 | - | - | - | - | - | <0.001 | |
| 63.3 | 61.6–64.8 | 1.36 | 1.22–1.52 | <0.001 | 0.50 | 0.39–0.64 | <0.001 | |||
| ARB | 65.0 | 63.6–66.5 | <0.001 | - | - | - | - | - | 0.007 | |
| 71.5 | 68.0–74.8 | 0.76 | 0.66–0.89 | <0.001 | 0.80 | 0.69–0.94 | 0.007 | |||
| Statin | 63.3 | 61.5–65.0 | <0.001 | - | - | - | - | - | <0.001 | |
| 69.8 | 67.8–71.8 | 0.77 | 0.70–0.85 | <0.001 | 0.81 | 0.73–0.91 | <0.001 | |||
| Fibrate | 65.7 | 64.3–67.0 | <0.001 | - | - | - | - | - | 0.525 | |
| 72.9 | 65.4–79.0 | 0.74 | 0.55–1.00 | 0.046 | 0.91 | 0.67–1.23 | 0.525 | |||
| Metformin | 65.4 | 64.0–66.8 | <0.001 | - | - | - | - | - | 0.181 | |
| 70.6 | 66.3–74.4 | 0.79 | 0.67–0.94 | 0.007 | 0.88 | 0.72–1.06 | 0.181 | |||
| DLD | 61.6 | 59.1–64.0 | <0.001 | - | - | - | - | - | 0.029 | |
| 68.0 | 66.4–69.5 | 0.79 | 0.72–0.88 | <0.001 | 0.88 | 0.78–0.99 | 0.029 | |||
| DM | 66.2 | 64.6–67.8 | 0.689 | - | - | - | - | - | 0.015 | |
| 65.4 | 63.1–67.7 | 1.02 | 0.92–1.13 | 0.690 | 0.86 | 0.75–0.97 | 0.015 | |||
Please refer to Supplemental Table 1 for size of group depicted in each row.
Abbreviations: ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; D+ACEi, disease and taking ACEi; DnACEi, disease and not taking ACEi; DLD, dyslipidemia; DM, diabetes mellitus; HR, hazard ratio; NCI, National Cancer Institute; nD, no disease; NOS, not otherwise specified; OS2, overall survival at two years; 95%CI, 95% confidence interval
Table 2.
Overall Survival, ARB cohort
| Kaplan-Meier | Cox Univariable Analysis | Cox Multivariable Analysis | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| OS2 (%) | 95%CI (%) | p (logrank) | HR | 95%CI | p (class) | HR | 95%CI | p (class) | p (variable) | |
| Disease/Drug Category | 72.2 | 68.6–75.4 | <0.001 | - | - | - | - | - | - | 0.002 |
| 63.6 | 62.0–65.3 | 1.41 | 1.21–1.64 | <0.001 | 1.28 | 1.09–1.51 | 0.003 | |||
| 70.0 | 67.2–72.7 | 1.10 | 0.92–1.32 | 0.291 | 1.09 | 0.89–1.33 | 0.426 | |||
| Age | 73.1 | 71.4–74.8 | <0.001 | - | - | - | - | - | - | <0.001 |
| 62.2 | 59.8–64.5 | 1.52 | 1.37–1.69 | <0.001 | 1.61 | 1.44–1.80 | <0.001 | |||
| 46.6 | 42.7–50.5 | 2.47 | 2.17–2.81 | <0.001 | 2.49 | 2.16–2.88 | <0.001 | |||
| Sex | 67.7 | 66.0–69.2 | <0.001 | - | - | - | - | - | - | 0.894 |
| 63.1 | 60.7–65.4 | 1.19 | 1.08–1.31 | 0.001 | 1.01 | 0.90–1.12 | 0.894 | |||
| Race | 67.3 | 65.9–68.8 | <0.001 | - | - | - | - | - | - | 0.518 |
| 61.0 | 57.8–64.0 | 1.24 | 1.10–1.39 | <0.001 | 1.04 | 0.92–1.18 | 0.518 | |||
| Marital Status | 72.8 | 70.9–74.5 | <0.001 | - | - | - | - | - | - | <0.001 |
| 59.8 | 57.9–61.7 | 1.63 | 1.48–1.80 | <0.001 | 1.32 | 1.19–1.47 | <0.001 | |||
| Geographic Region | 67.1 | 65.0–69.1 | 0.017 | - | - | - | - | - | - | 0.390 |
| 67.8 | 64.7–70.7 | 0.98 | 0.86–1.13 | 0.798 | 0.95 | 0.81–1.11 | 0.496 | |||
| 67.0 | 63.1–70.6 | 1.01 | 0.87–1.18 | 0.877 | 1.06 | 0.89–1.26 | 0.513 | |||
| 63.2 | 60.6–65.6 | 1.18 | 1.05–1.32 | 0.005 | 1.08 | 0.94–1.23 | 0.271 | |||
| Population Density | 66.2 | 64.7–67.7 | 0.560 | - | - | - | - | - | - | 0.801 |
| 65.3 | 62.1–68.3 | 1.04 | 0.92–1.17 | 0.554 | 0.89 | 0.63–1.25 | 0.505 | |||
| 69.6 | 60.5–77.0 | 0.87 | 0.63–1.21 | 0.400 | 0.99 | 0.86–1.14 | 0.907 | |||
| Year of Diagnosis | 63.2 | 58.9–67.2 | 0.037 | - | - | - | - | - | - | 0.019 |
| 63.9 | 59.7–67.8 | 0.97 | 0.79–1.18 | 0.739 | 0.96 | 0.79–1.18 | 0.710 | |||
| 61.7 | 57.5–65.6 | 1.04 | 0.86–1.27 | 0.688 | 1.01 | 0.83–1.24 | 0.904 | |||
| 67.2 | 63.3–70.7 | 0.87 | 0.71–1.06 | 0.468 | 0.80 | 0.66–0.98 | 0.030 | |||
| 67.3 | 63.5–70.7 | 0.87 | 0.71–1.05 | 0.147 | 0.84 | 0.69–1.03 | 0.094 | |||
| 68.3 | 64.7–71.6 | 0.82 | 0.68–1.00 | 0.047 | 0.87 | 0.71–1.05 | 0.150 | |||
| 69.8 | 66.5–72.8 | 0.79 | 0.65–0.95 | 0.013 | 0.75 | 0.62–0.91 | 0.004 | |||
| 56.5 | 50.3–62.2 | 0.92 | 0.76–1.11 | 0.384 | 0.90 | 0.74–1.11 | 0.322 | |||
| Primary Site | 64.1 | 61.3–66.7 | <0.001 | - | - | - | - | - | - | <0.001 |
| 82.1 | 77.0–86.2 | 0.43 | 0.32–0.58 | <0.001 | 0.52 | 0.38–0.70 | <0.001 | |||
| 59.4 | 51.3–66.6 | 1.10 | 0.85–1.42 | 0.479 | 0.74 | 0.57–0.97 | 0.030 | |||
| 67.0 | 64.3–69.6 | 0.92 | 0.80–1.05 | 0.193 | 0.62 | 0.53–0.73 | <0.001 | |||
| 66.4 | 55.3–57.3 | 0.96 | 0.66–1.40 | 0.839 | 0.66 | 0.45–0.99 | 0.042 | |||
| 45.1 | 38.5–51.5 | 1.74 | 1.43–2.13 | <0.001 | 0.97 | 0.78–1.22 | 0.812 | |||
| 68.9 | 66.4–71.2 | 0.84 | 0.74–0.96 | 0.010 | 0.75 | 0.64–0.88 | 0.001 | |||
| 62.1 | 56.3–67.3 | 1.08 | 0.88–1.32 | 0.464 | 1.00 | 0.81–1.23 | 0.995 | |||
| T-Classification | 82.8 | 80.9–84.6 | <0.001 | - | - | - | - | - | - | <0.001 |
| 65.1 | 62.5–67.5 | 2.25 | 1.95–2.60 | <0.001 | 1.78 | 1.28–2.46 | 0.001 | |||
| 52.6 | 48.8–56.3 | 3.46 | 2.95–4.05 | <0.001 | 3.37 | 2.38–4.78 | <0.001 | |||
| 43.7 | 40.2–47.2 | 4.48 | 3.86–5.20 | <0.001 | 4.28 | 3.08–5.94 | <0.001 | |||
| 65.1 | 60.2–69.4 | 2.34 | 1.92–2.86 | <0.001 | 2.81 | 1.98–3.65 | <0.001 | |||
| N-Classification | 74.1 | 72.4–75.6 | <0.001 | - | - | - | - | - | - | <0.001 |
| 55.0 | 51.1–58.6 | 1.99 | 1.75–2.28 | <0.001 | 1.84 | 1.59–2.13 | <0.001 | |||
| 54.5 | 51.7–57.3 | 2.03 | 1.82–2.26 | <0.001 | 2.12 | 1.85–2.43 | <0.001 | |||
| 47.8 | 37.5–57.4 | 2.55 | 1.92–3.40 | <0.001 | 2.69 | 1.98–3.65 | <0.001 | |||
| Comorbidity Index | 73.8 | 71.8–75.7 | <0.001 | - | - | - | - | - | - | <0.001 |
| 68.9 | 66.4–71.3 | 1.23 | 1.08–1.40 | 0.002 | 1.28 | 1.12–1.47 | <0.001 | |||
| 55.0 | 52.5–57.4 | 1.98 | 1.76–2.21 | <0.001 | 1.99 | 1.74–2.29 | <0.001 | |||
| 59.3 | 49.3–68.0 | 1.76 | 1.29–2.40 | <0.001 | 1.07 | 0.77–1.49 | 0.695 | |||
| Facility Type | 63.4 | 61.4–65.4 | <0.001 | - | - | - | - | - | - | <0.001 |
| 72.4 | 68.9–75.6 | 0.70 | 0.60–0.83 | <0.001 | 0.71 | 0.60–0.84 | <0.001 | |||
| 66.9 | 64.8–68.8 | 0.90 | 0.81–0.99 | 0.034 | 0.90 | 0.80–1.00 | 0.045 | |||
| Tract % High School Only | 68.4 | 66.5–70.2 | <0.001 | - | - | - | - | - | - | 0.154 |
| 63.9 | 61.9–65.7 | 1.19 | 1.08–1.31 | <0.001 | 1.09 | 0.97–1.23 | 0.154 | |||
| Tract % Below Poverty | 69.3 | 67.4–71.0 | <0.001 | - | - | - | - | - | - | 0.124 |
| 63.0 | 61.1–64.9 | 1.26 | 1.14–1.38 | <0.001 | 1.09 | 0.98–1.22 | 0.124 | |||
| Surgery | 61.0 | 59.1–62.9 | <0.001 | - | - | - | - | - | - | <0.001 |
| 71.7 | 69.9–73.5 | 0.67 | 0.61–0.74 | <0.001 | 0.62 | 0.55–0.71 | <0.001 | |||
| Chemotherapy | 71.3 | 69.6–72.9 | <0.001 | - | - | - | - | - | - | 0.514 |
| 58.9 | 56.8–61.0 | 1.53 | 1.39–1.68 | <0.001 | 0.96 | 0.84–1.09 | 0.514 | |||
| Radiotherapy | 72.2 | 69.9–74.4 | <0.001 | - | - | - | - | - | - | <0.001 |
| 63.5 | 61.8–65.1 | 1.35 | 1.21–1.51 | <0.001 | 0.51 | 0.40–0.64 | <0.001 | |||
| ACEi | 65.1 | 63.5–66.6 | 0.006 | - | - | - | - | - | - | 0.047 |
| 69.0 | 66.4–71.5 | 0.86 | 0.77–0.96 | 0.007 | 0.89 | 0.78–1.00 | 0.047 | |||
| Statin | 63.4 | 61.6–65.1 | <0.001 | - | - | - | - | - | - | <0.001 |
| 70.1 | 68.0–72.0 | 0.77 | 0.69–0.85 | <0.001 | 0.81 | 0.73–0.91 | <0.001 | |||
| Fibrate | 65.9 | 64.5–67.2 | 0.028 | - | - | - | - | - | - | 0.394 |
| 73.6 | 66.3–79.6 | 0.72 | 0.54–0.97 | 0.030 | 0.88 | 0.65–1.19 | 0.394 | |||
| Metformin | 65.6 | 64.2–67.0 | 0.009 | - | - | - | - | - | - | 0.214 |
| 70.5 | 66.2–74.3 | 0.80 | 0.68–0.95 | 0.010 | 0.89 | 0.73–1.07 | 0.214 | |||
| DLD | 62.0 | 59.5–64.3 | <0.001 | - | - | - | - | - | - | 0.029 |
| 68.1 | 66.5–69.6 | 0.80 | 0.72–0.88 | <0.001 | 0.88 | 0.78–0.99 | 0.029 | |||
| DM | 66.5 | 64.8–68.0 | 0.568 | - | - | - | - | - | - | 0.018 |
| 65.4 | 63.0–67.7 | 1.03 | 0.93–1.14 | 0.570 | 0.86 | 0.76–0.97 | 0.018 | |||
Please refer to Supplemental Table 2 for size of group depicted in each row.
Abbreviations: ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; D+ARB; disease and taking ARB; DnARB, disease and not taking ARB; DLD, dyslipidemia; DM, diabetes mellitus; HR, hazard ratio; NCI, National Cancer Institute; nD, no disease; NOS, not otherwise specified; OS2, overall survival at two years; 95%CI, 95% confidence interval
Table 3.
Cancer-Specific Survival, ACEi cohort
| Kaplan-Meier | Cox Univariable Analysis | Cox Multivariable Analysis | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| CSS2 (%) | 95%CI (%) | p (logrank) | HR | 95%CI | p (class) | HR | 95%CI | p (class) | p (variable) | |
| D+ACEi | 76.6 | 73.9–79.1 | 0.024 | - | - | - | - | - | . | 0.565 |
| DnACEi | 73.0 | 71.1–74.8 | 1.22 | 1.05–1.42 | 0.008 | 1.06 | 0.91–1.25 | 0.441 | ||
| nD | 74.4 | 71.3–77.2 | 1.11 | 0.93–1.33 | 0.261 | 0.98 | 0.79–1.21 | 0.837 | ||
| 66–74 | 79.0 | 77.2–80.6 | <0.001 | - | - | - | - | - | - | <0.001 |
| 75–84 | 71.6 | 69.1–74.0 | 1.44 | 1.26–1.65 | <0.001 | 1.59 | 1.39–1.83 | <0.001 | ||
| 85+ | 59.2 | 54.6–63.5 | 2.29 | 1.94–2.70 | <0.001 | 2.48 | 2.07–2.99 | <0.001 | ||
| Male | 76.8 | 75.2–78.4 | <0.001 | - | - | - | - | - | 0.002 0.445 |
|
| Female | 69.0 | 66.5–82.0 | 1.42 | 1.26–1.61 | <0.001 | 1.24 | 1.08–1.42 | 0.002 | ||
| White | 45.5 | 73.9–76.9 | <0.001 | - | - | - | - | - | - | |
| Black | 69.0 | 65.5–72.1 | 1.28 | 1.11–1.48 | 0.001 | 1.06 | 0.91–1.24 | 0.445 | 0.001 | |
| Married/Partnered | 79.1 | 77.2–80.9 | <0.001 | - | - | - | - | - | - | |
| Non-Married | 69.4 | 67.4–71.4 | 1.60 | 1.41–1.80 | <0.001 | 1.25 | 1.10–1.43 | 0.001 | ||
| West | 73.4 | 71.1–75.5 | 0.023 | - | - | - | - | - | - | 0.053 |
| East | 78.2 | 75.0–80.9 | 0.82 | 0.68–0.97 | 0.025 | 0.77 | 0.63–0.93 | 0.008 | ||
| Midwest | 74.3 | 70.2–78.0 | 0.99 | 0.82–1.21 | 0.929 | 0.99 | 0.79–1.22 | 0.888 | ||
| South | 72.7 | 70.0–75.1 | 1.09 | 0.94–1.26 | 0.239 | 0.96 | 0.81–1.13 | 0.598 | ||
| Metropolitan | 74.4 | 72.8–75.8 | 0.829 | - | - | - | - | - | - | 0.671 |
| Urban | 73.5 | 70.1–76.6 | 1.05 | 0.90–1.23 | 0.540 | 1.20 | 0.80–1.79 | 0.375 | ||
| Rural | 73.7 | 63.9–81.3 | 1.02 | 0.70–1.50 | 0.905 | 1.02 | 0.86–1.22 | 0.791 | ||
| 2008 | 73.9 | 69.7–77.6 | 0.538 | - | - | - | - | - | - | 0.197 |
| 2009 | 72.8 | 68.7–76.5 | 1.05 | 0.83–1.34 | 0.675 | 1.05 | 0.82–1.34 | 0.711 | ||
| 2010 | 71.1 | 67.0–74.9 | 1.11 | 0.87–1.41 | 0.410 | 1.08 | 0.85–1.38 | 0.538 | ||
| 2011 | 74.5 | 70.8–77.9 | 0.97 | 0.77–1.24 | 0.826 | 0.86 | 0.68–1.10 | 0.230 | ||
| 2012 | 73.7 | 70.0–77.1 | 1.00 | 0.79–1.26 | 0.985 | 0.95 | 0.75–1.20 | 0.639 | ||
| 2013 | 75.2 | 71.7–78.4 | 0.93 | 0.73–1.17 | 0.523 | 0.96 | 0.76–1.22 | 0.758 | ||
| 2014 | 76.5 | 72.2–80.2 | 0.90 | 0.71–1.15 | 0.408 | 0.83 | 0.65–1.06 | 0.130 | ||
| 2015 | 89.5 | 85.6–92.3 | 0.81 | 0.58–1.15 | 0.242 | 0.76 | 0.54–1.08 | 0.130 | ||
| Oral Cavity | 70.7 | 67.7–73.4 | <0.001 | - | - | - | - | - | - | <0.001 |
| Lip | 93.4 | 89.1–96.1 | 0.18 | 0.11–0.31 | <0.001 | 0.26 | 0.15–0.46 | <0.001 | ||
| Salivary Glands | 72.8 | 63.6–80.0 | 0.89 | 0.62–1.27 | 0.513 | 0.63 | 0.43–0.91 | 0.013 | ||
| Oropharynx | 73.6 | 70.7–76.2 | 0.91 | 0.77–1.08 | 0.271 | 0.58 | 0.48–0.71 | <0.001 | ||
| Nasopharynx | 70.7 | 58.5–80.0 | 1.03 | 0.66–1.60 | 0.909 | 0.64 | 0.40–1.02 | 0.061 | ||
| Hypopharynx | 51.7 | 43.8–58.9 | 1.79 | 0.41–2.27 | <0.001 | 0.96 | 0.73–1.25 | 0.749 | ||
| Larynx | 79.0 | 76.6–81.2 | 0.69 | 0.59–0.82 | <0.001 | 0.67 | 0.55–0.82 | <0.001 | ||
| Overlapping/NOS | 67.1 | 60.8–72.6 | 1.14 | 0.90–1.46 | 0.282 | 1.06 | 0.83–1.36 | 0.632 | ||
| T0–1 | 89.0 | 87.3–90.6 | <0.001 | - | - | - | - | - | - | <0.001 |
| T2 | 73.4 | 70.7–76.0 | 2.61 | 2.15–3.17 | <0.001 | 1.76 | 1.16–2.69 | 0.008 | ||
| T3 | 60.3 | 56.0–64.3 | 4.49 | 3.65–5.51 | <0.001 | 4.08 | 2.63–6.31 | <0.001 | ||
| T4 | 52.2 | 48.1–56.2 | 5.79 | 4.76–7.03 | <0.001 | 4.89 | 3.22–7.42 | <0.001 | ||
| Unknown | 76.1 | 71.2–80.2 | 2.58 | 1.98–3.36 | <0.001 | 4.03 | 2.38–6.84 | <0.001 | ||
| N0 | 82.9 | 81.4–84.4 | <0.001 | - | - | - | - | - | - | <0.001 |
| N1 | 61.6 | 57.4–65.6 | 2.59 | 2.20–3.05 | <0.001 | 2.21 | 1.85–2.65 | <0.001 | ||
| N2 | 60.7 | 57.5–63.8 | 2.65 | 2.31–3.04 | <0.001 | 2.46 | 2.08–2.92 | <0.001 | ||
| N3 | 54.7 | 42.5–65.4 | 3.30 | 2.34–4.86 | <0.001 | 3.15 | 2.17–4.55 | <0.001 | ||
| 0 | 78.4 | 76.3–80.4 | <0.001 | - | - | - | - | - | - | <0.001 |
| 1 | 76.3 | 73.6–78.7 | 1.13 | 0.96–1.32 | 0.148 | 1.16 | 0.98–1.38 | 0.085 | ||
| 2 | 67.9 | 65.3–70.5 | 1.64 | 1.43–1.89 | <0.001 | 1.70 | 1.43–2.02 | <0.001 | ||
| Unknown | 61.6 | 50.4–71.0 | 2.02 | 1.42–2.88 | 1.11 | 0.76–1.63 | 0.576 | |||
| Other | 73.9 | 71.7–75.9 | 0.184 | - | - | - | - | - | - | 0.084 |
| NCI Center | 76.5 | 72.7–79.9 | 0.85 | 0.70–1.03 | 0.092 | 0.80 | 0.65–0.98 | 0.035 | ||
| Teaching Hospital | 73.8 | 71.6–75.8 | 1.01 | 0.89–1.15 | 0.913 | 0.99 | 0.87–1.14 | 0.910 | ||
| ≤ median | 75.9 | 74.0–77.8 | 0.004 | - | - | - | - | - | - | 0.075 |
| > median | 72.5 | 70.5–74.4 | 1.19 | 1.06–1.34 | 0.005 | 1.15 | 0.99–1.33 | 0.075 | ||
| ≤ median | 77.3 | 75.3–79.1 | <0.001 | - | - | - | - | - | - | 0.106 |
| > median | 71.2 | 69.2–73.1 | 1.33 | 1.18–1.50 | <0.001 | 1.12 | 0.98–1.29 | 0.106 | ||
| No | 70.3 | 68.3–72.2 | <0.001 | - | - | - | - | - | - | <0.001 |
| Yes | 78.6 | 76.6–80.4 | 0.66 | 0.58–0.74 | <0.001 | 0.64 | 0.54–0.76 | <0.001 | ||
| No | 80.3 | 78.6–81.8 | <0.001 | - | - | - | - | - | - | 0.631 |
| Yes | 65.5 | 63.1–67.8 | 1.84 | 1.63–2.07 | <0.001 | 1.04 | 0.89–1.22 | 0.631 | ||
| No | 82.0 | 79.6–84.1 | <0.001 | - | - | - | - | - | - | <0.001 |
| Yes | 71.2 | 69.5–72.9 | 1.60 | 1.38–1.86 | <0.001 | 0.54 | 0.40–0.74 | <0.001 | ||
| No | 73.7 | 72.1–75.1 | 0.019 | - | - | - | - | - | - | 0.060 |
| Yes | 77.5 | 73.7–80.8 | 0.80 | 0.67–0.97 | 0.020 | 0.83 | 0.68–1.01 | 0.060 | ||
| No | 71.2 | 69.4–73.0 | <0.001 | - | - | - | - | - | - | <0.001 |
| Yes | 78.4 | 76.3–80.4 | 0.70 | 0.62–0.80 | <0.001 | 0.75 | 0.65–0.87 | <0.001 | ||
| No | 74.1 | 72.7–75.4 | 0.217 | - | - | - | - | - | - | 0.770 |
| Yes | 77.6 | 69.1–84.0 | 0.80 | 0.55–1.15 | 0.222 | 1.06 | 0.73–1.54 | 0.770 | ||
| No | 73.7 | 72.2–75.1 | 0.010 | - | - | - | - | - | - | 0.277 |
| Yes | 78.5 | 74.0–82.3 | 0.75 | 0.60–0.94 | 0.011 | 0.87 | 0.68–1.12 | 0.277 | ||
| No | 69.4 | 66.7–71.9 | <0.001 | - | - | - | - | - | - | 0.095 |
| Yes | 76.4 | 74.8–77.9 | 0.75 | 0.66–0.85 | <0.001 | 0.88 | 0.76–1.02 | 0.095 | ||
| No | 74.1 | 72.4–75.8 | 0.894 | - | - | - | - | - | - | 0.304 |
| Yes | 74.3 | 71.8–76.6 | 0.99 | 0.87–1.13 | 0.895 | 0.92 | 0.78–1.08 | 0.304 | ||
Please refer to Supplemental Table 1 for size of group depicted in each row.
Abbreviations: ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; CSS2, cancer-specific survival at two years; D+ACEi, disease and taking ACEi; DnACEi, disease and not taking ACEi; DLD, dyslipidemia; DM, diabetes mellitus; HR, hazard ratio; NCI, National Cancer Institute; nD, no disease; NOS, not otherwise specified; 95%CI, 95% confidence interval
Table 4.
Cancer-Specific Survival, ARB cohort
| Kaplan-Meier | Cox Univariable Analysis | Cox Multivariable Analysis | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| CSS2 (%) | 95%CI (%) | p (logrank) | HR | 95%CI | p (class) | HR | 95%CI | p (class) | p (variable) | |
| D+ARB | 77.9 | 74.1–81.2 | 0.026 | - | - | - | - | - | - | 0.107 |
| DnARB | 73.4 | 71.7–75.0 | 1.29 | 1.06–1.57 | 0.010 | 1.23 | 1.00–1.50 | 0.050 | ||
| nD | 74.8 | 71.8–77.6 | 1.18 | 0.94–1.47 | 0.150 | 1.11 | 0.86–1.42 | 0.426 | ||
| 66–74 | 79.2 | 77.4–80.8 | <0.001 | - | - | - | - | - | - | <0.001 |
| 75–84 | 71.7 | 69.2–74.0 | 1.45 | 1.27–1.66 | <0.001 | 1.60 | 1.40–1.84 | <0.001 | ||
| 85+ | 59.0 | 54.4–63.3 | 2.34 | 1.99–2.75 | <0.001 | 2.54 | 2.11–3.05 | <0.001 | ||
| Male | 46.9 | 75.3–78.5 | <0.001 | - | - | - | - | - | - | 0.002 |
| Female | 69.1 | 66.6–71.5 | 1.42 | 1.26–1.61 | <0.001 | 1.24 | 1.08–1.42 | 0.002 | ||
| White | 75.5 | 74.0–77.0 | <0.001 | - | - | - | - | - | - | 0.462 |
| Black | 69.1 | 65.7–72.2 | 1.28 | 1.11–1.47 | 0.001 | 1.06 | 0.91–1.24 | 0.462 | ||
| Married/Partnered | 79.3 | 77.4–87.0 | <0.001 | - | - | - | - | - | - | 0.001 |
| Non-Married | 69.5 | 67.4–71.4 | 1.61 | 1.42–1.81 | <0.001 | 1.25 | 1.10–1.43 | 0.001 | ||
| West | 73.5 | 71.3–75.6 | 0.028 | - | - | - | - | - | - | 0.060 |
| East | 78.0 | 74.9–80.8 | 0.83 | 0.69–0.98 | 0.032 | 0.77 | 0.63–0.94 | 0.009 | ||
| Midwest | 74.9 | 70.8–78.5 | 0.97 | 0.80–1.19 | 0.792 | 0.97 | 0.78–1.21 | 0.803 | ||
| South | 72.7 | 70.1–75.2 | 1.09 | 0.95–1.26 | 0.232 | 0.96 | 0.81–1.13 | 0.588 | ||
| Metropolitan | 74.4 | 72.9–75.9 | 0.809 | - | - | - | - | - | - | 0.849 |
| Urban | 73.6 | 70.2–76.6 | 1.05 | 0.90–1.22 | 0.551 | 1.12 | 0.74–1.68 | 0.592 | ||
| Rural | 75.0 | 65.4–82.4 | 0.96 | 0.65–1.42 | 0.838 | 1.03 | 0.86–1.22 | 0.769 | ||
| 2008 | 73.9 | 69.7–77.6 | 0.515 | - | - | - | - | - | - | 0.247 |
| 2009 | 72.8 | 68.7–76.5 | 1.05 | 0.83–1.34 | 0.673 | 1.05 | 0.82–1.34 | 0.693 | ||
| 2010 | 71.2 | 67.0–74.9 | 1.11 | 0.87–1.40 | 0.410 | 1.08 | 0.85–1.37 | 0.542 | ||
| 2011 | 74.7 | 70.9–78.0 | 0.97 | 0.76–1.23 | 0.794 | 0.86 | 0.67–1.09 | 0.216 | ||
| 2012 | 73.9 | 70.2–77.2 | 0.99 | 0.78–1.25 | 0.932 | 0.94 | 0.74–1.19 | 0.614 | ||
| 2013 | 75.6 | 72.1–78.7 | 0.92 | 0.72–1.16 | 0.458 | 0.96 | 0.76–1.21 | 0.715 | ||
| 2014 | 77.0 | 73.0–80.5 | 0.91 | 0.72–1.16 | 0.454 | 0.85 | 0.67–1.09 | 0.202 | ||
| 2015 | 89.6 | 85.8–92.4 | 0.81 | 0.57–1.14 | 0.219 | 0.76 | 0.53–1.08 | 0.126 | ||
| Oral Cavity | 70.7 | 67.7–73.4 | <0.001 | - | - | - | - | - | - | <0.001 |
| Lip | 93.5 | 89.2–96.1 | 0.18 | 0.11–0.31 | <0.001 | 0.26 | 0.15–0.45 | <0.001 | ||
| Salivary Glands | 73.3 | 64.2–80.3 | 0.87 | 0.61–1.25 | 0.460 | 0.63 | 0.43–0.91 | 0.013 | ||
| Oropharynx | 73.6 | 70.7–76.2 | 0.91 | 0.78–1.08 | 0.278 | 0.58 | 0.48–0.71 | <0.001 | ||
| Nasopharynx | 72.0 | 59.8–81.1 | 0.96 | 0.61–1.51 | 0.869 | 0.58 | 0.36–0.93 | 0.024 | ||
| Hypopharynx | 51.2 | 43.4–58.5 | 1.79 | 1.41–2.26 | <0.001 | 0.96 | 0.73–1.25 | 0.743 | ||
| Larynx | 79.2 | 76.8–81.3 | 0.69 | 0.58–0.81 | <0.001 | 0.66 | 0.54–0.81 | <0.001 | ||
| Overlapping/NOS | 67.7 | 61.4–73.2 | 1.12 | 0.88–1.43 | 0.355 | 1.04 | 0.81–1.33 | 0.746 | ||
| T0–1 | 88.9 | 87.1–90.5 | <0.001 | - | - | - | - | - | - | <0.001 |
| T2 | 73.5 | 70.8–76.1 | 2.57 | 2.12–3.12 | <0.001 | 1.80 | 1.18–2.74 | 0.006 | ||
| T3 | 60.7 | 56.4–64.7 | 4.36 | 3.56–5.35 | <0.001 | 4.03 | 2.60–6.24 | <0.001 | ||
| T4 | 52.4 | 48.3–56.4 | 5.71 | 4.71–6.93 | <0.001 | 5.04 | 3.33–7.63 | <0.001 | ||
| Unknown | 76.2 | 71.3–80.3 | 2.54 | 1.95–3.30 | <0.001 | 4.12 | 2.44–6.97 | <0.001 | ||
| N0 | 78.5 | 81.4–84.4 | <0.001 | - | - | - | - | - | - | <0.001 |
| N1 | 76.4 | 57.5–65.7 | 2.59 | 2.20–3.05 | <0.001 | 2.22 | 1.86–2.66 | <0.001 | ||
| N2 | 67.9 | 57.6–63.9 | 2.65 | 2.31–3.04 | <0.001 | 2.49 | 2.10–2.95 | <0.001 | ||
| N3 | 62.2 | 42.1–64.6 | 3.41 | 2.44–4.77 | <0.001 | 3.31 | 2.30–4.76 | <0.001 | ||
| 0 | 78.5 | 76.4–80.5 | <0.001 | - | - | - | - | - | - | <0.001 |
| 1 | 76.4 | 73.8–78.8 | 1.12 | 0.96–1.32 | 0.153 | 1.15 | 0.97–1.37 | 0.108 | ||
| 2 | 67.9 | 65.2–70.4 | 1.65 | 1.43–1.90 | <0.001 | 1.69 | 1.43–2.01 | <0.001 | ||
| Unknown | 62.2 | 51.1–71.5 | 2.02 | 1.42–2.87 | <0.001 | 1.13 | 0.78–1.66 | 0.517 | ||
| Other | 73.8 | 71.7–75.8 | 0.235 | - | - | - | - | - | - | 0.093 |
| NCI Center | 76.4 | 72.6–79.8 | 0.85 | 0.71–1.04 | 0.108 | 0.81 | 0.66–0.99 | 0.040 | ||
| Teaching Hospital | 74.0 | 71.9–76.0 | 1.00 | 0.88–1.13 | 0.971 | 0.99 | 0.87–1.14 | 0.940 | ||
| ≤ median | 76.0 | 74.1–77.8 | 0.005 | - | - | - | - | - | - | 0.062 |
| > median | 72.6 | 70.6–74.5 | 1.19 | 1.05–1.34 | 0.005 | 1.15 | 0.99–1.34 | 0.062 | ||
| ≤ median | 77.2 | 75.3–79.0 | <0.001 | - | - | - | - | - | - | 0.137 |
| > median | 71.4 | 69.4–73.3 | 1.31 | 1.17–1.48 | <0.001 | 1.11 | 0.97–1.28 | 0.137 | ||
| No | 70.4 | 68.4–72.3 | <0.001 | - | - | - | - | - | - | <0.001 |
| Yes | 78.6 | 76.7–80.4 | 0.66 | 0.58–0.74 | <0.001 | 0.64 | 0.54–0.75 | <0.001 | ||
| No | 80.4 | 78.8–82.0 | <0.001 | - | - | - | - | - | - | 0.653 |
| Yes | 65.6 | 63.2–67.8 | 1.84 | 1.63–2.08 | <0.001 | 1.04 | 0.88–1.22 | 0.653 | ||
| No | 82.0 | 79.7–84.1 | <0.001 | - | - | - | - | - | - | <0.001 |
| Yes | 71.3 | 69.7–73.0 | 1.60 | 1.38–1.85 | <0.001 | 0.54 | 0.40–0.74 | <0.001 | ||
| No | 73.4 | 71.8–75.0 | 0.012 | - | - | - | - | - | - | 0.332 |
| Yes | 76.7 | 74.1–79.2 | 0.84 | 0.73–0.96 | 0.013 | 0.93 | 0.80–1.08 | 0.332 | ||
| No | 71.4 | 69.5–73.2 | 0.016 | - | - | - | - | - | - | <0.001 |
| Yes | 78.4 | 76.4–80.3 | 0.70 | 0.62–0.80 | <0.001 | 0.76 | 0.66–0.88 | <0.001 | ||
| No | 74.1 | 72.7–75.5 | <0.001 | - | - | - | - | - | - | 0.963 |
| Yes | 78.2 | 69.9–84.5 | 0.77 | 0.54–1.12 | 0.173 | 1.01 | 0.69–1.47 | 0.963 | ||
| No | 73.9 | 72.4–75.3 | 0.168 | - | - | - | - | - | - | 0.372 |
| Yes | 78.0 | 73.5–81.8 | 0.77 | 0.62–0.96 | 0.019 | 0.89 | 0.70–1.14 | 0.372 | ||
| No | 69.7 | 67.1–72.2 | 0.018 | - | - | - | - | - | - | 0.100 |
| Yes | 76.4 | 74.8–78.0 | 0.75 | 0.67–0.85 | <0.001 | 0.89 | 0.77–1.02 | 0.100 | ||
| No | 74.3 | 72.6–75.9 | 0.799 | - | - | - | - | - | - | 0.305 |
| Yes | 74.2 | 71.7–76.5 | 1.00 | 0.88–1.14 | 0.999 | 0.92 | 0.78–1.08 | 0.305 | ||
Please refer to Supplemental Table 2 for size of group depicted in each row.
Abbreviations: ACEi, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; CSS2, cancer-specific survival at two years; D+ARB; disease and taking ARB; DnARB, disease and not taking ARB; DLD, dyslipidemia; DM, diabetes mellitus; HR, hazard ratio; NCI, National Cancer Institute; nD, no disease; NOS, not otherwise specified; 95%CI, 95% confidence interval
Association of ACEi with OS
Kaplan-Meier estimates of two-year OS were highest among nD at 69.4%, intermediate among D+ACEi at 68.7%, and lowest among DnACEi at 63.5% (Figure 2a). On Cox univariable regression, OS was not significantly different for nD as compared to D+ACEi (HR 0.98, 95%CI 0.84–1.13, p=0.742) but was significantly worse for DnACEi (HR 1.23, 95%CI 1.09–1.38, p<0.001).
Figure 2a.
Kaplan-Meier curves depicting overall survival by ACEi and relevant disease status. Blue, no chronic kidney disease or hypertension; Red, chronic kidney disease or hypertension and not taking ACEi; Green, chronic kidney disease or hypertension and taking ACEi
After multivariable adjustment, OS was numerically but not significantly worse for DnACEi as compared to D+ACEi (HR 1.12, 95%CI 0.99–1.27, p=0.067) and not significantly different for nD (HR 0.98, 95%CI 0.82–1.16, p=0.796). Other factors associated with worse OS on Cox MVA were older age, non-married status, earlier year of diagnosis, oral cavity primary site, advanced T- and N-classification, higher comorbidity index, non-NCI and non-teaching facility type, and non-receipt of surgery, radiotherapy, or statin therapy.
Association of ACEi with CSS
In contrast to Kaplan-Meier estimates for OS, the group with the highest two-year CSS was D+ACEi at 76.6%, followed by nD at 74.4%, and then DnACEi at 73.0% (Figure 2b). Cox univariable regression demonstrated non-significantly worse CSS among nD (HR 1.11, 95%CI 0.93–1.33, p=0.261) and significantly worse OS among DnACEi (HR 1.22, 95%CI 1.05–1.42, p=0.008) as compared to D+ACEi.
Figure 2b.
Kaplan-Meier curves depicting cancer-specific survival by ACEi and relevant disease status. Blue, no chronic kidney disease or hypertension; Red, chronic kidney disease or hypertension and not taking ACEi; Green, chronic kidney disease or hypertension and taking ACEi
On Cox multivariable regression, CSS did not significantly differ for DnACEi (HR 1.06, 95%CI 0.91–1.25, p=0.441) or nD (HR 0.98, 95%CI 0.79–1.21, p=0.837) as compared to D+ACEi. Other factors associated with worse CSS on Cox MVA included older age, female gender, non-married status, oral cavity primary site, advanced T- and N-classification, high comorbidity index, and non-receipt of surgery, radiotherapy, or statin therapy.
Association of ARB with OS
Two-year OS rates were highest among D+ARB at 72.2%, followed closely by nD at 70.0%, and lowest among DnARB at 63.6% (Figure 2c). Univariable Cox regression results were consistent, with non-significantly worse OS among nD (HR 1.10, 95%CI 0.92–1.32, p=0.291) but significantly worse OS among DnARB (HR 1.41, 95%CI 1.21–1.64, p<0.001) as compared to D+ARB.
Figure 2c.
Kaplan-Meier curves depicting overall survival by ARB and relevant disease status. Blue, no chronic kidney disease or hypertension; Red, chronic kidney disease or hypertension and not taking ACEi; Green, chronic kidney disease or hypertension and taking ACEi
These findings persisted on Cox MVA. As compared to D+ARB, OS was non-significantly worse among nD (HR 1.09, 95%CI 0.89–1.33, p=0.426) and significantly worse among DnARB (HR 1.28, 95%CI 1.09–1.51, p=0.003). In addition, older age, non-married status, oral cavity primary site, advanced T- and N-classification, higher comorbidity index, non-NCI and non-teaching facility type, and non-receipt of surgery, radiotherapy, or statin therapy were all independently associated with worse OS.
Association of ARB with CSS
As for OS, Kaplan-Meier estimates for two-year CSS were highest among D+ARB at 77.9%, followed by nD at 74.8%, and then DnARB at 73.4% (Figure 2d). On Cox univariable regression, CSS was numerically but not significantly worse for nD as compared to D+ARB (HR 1.18, 95%CI 0.94–1.47, p=0.150) but was significantly worse for DnARB (HR 1.29, 95%CI 1.06–1.57, p=0.010).
Figure 2d.
Kaplan-Meier curves depicting cancer-specific survival by ARB and relevant disease status. Blue, no chronic kidney disease or hypertension; Red, chronic kidney disease or hypertension and not taking ACEi; Green, chronic kidney disease or hypertension and taking ACEi
Similar findings were again found on Cox MVA, with no significant difference in CSS among nD (HR 1.11, 95%CI 0.86–1.42, p=0.426) but significantly worse CSS among DnARB (HR 1.23, 95%CI 1.00–1.50, p=0.050) as compared to D+ARB. Other factors associated with worse CSS on Cox MVA included older age, female gender, non-married status, oral cavity primary site, advanced T- and N-classification, high comorbidity index, and non-receipt of surgery, radiotherapy, or statin therapy.
Subgroup Analysis
No significant associations between disease/ARB status and OS or CSS were identified in sixteen subgroups (all p≥0.010) (Supplemental Figures 1 & 2). However, favorable HR and 95%CI were observed for both OS and CSS among patients receiving radiotherapy, those forgoing surgery, and those with node-positive disease.
Discussion:
In the largest study to date evaluating the impact of RAS inhibitors in HNC, we identified significantly improved OS and CSS with ARB, but not with ACEi. Subgroup analysis did not distinguish any population for whom ARB receipt was significantly associated with survival, which may reflect limitations in statistical power.
Upregulation of RAS signaling has been characterized in a variety of cancers and is mediated through activity of angiotensin II at angiotensin receptors 1 and 2 (AT1R and AT2R, respectively). A recent preclinical study identified upregulation of AT1R in HNC cells and demonstrated increased capacity of these cells for migration and invasion upon exposure to angiotensin II5. Earlier studies demonstrated that angiotensin II promotes expression of vascular endothelial growth factor (VEGF) in both tumor cells and the tumor microenvironment15,16, leading to angiogenesis. Meanwhile, AT2R activation by angiotensin II has been implicated in both VEGF expression and proliferation by tumor cells17. While at this time it is unknown which pathways contribute to HNC oncogenesis, their common mediator in angiotensin II presents an attractive therapeutic target.
Our observation of significant differences in survival with ARB but not ACEi are intriguing in light of the similarities between these drug classes. ACEi and ARB target adjacent steps in the RAS signaling pathway; however, they are pharmacologically distinct. Pertinently, ACEi act upstream of ARB, preventing conversion of angiotensin I to angiotensin II, while ARB inhibit the angiotensin II type I receptor. Importantly, angiotensin II can be produced by kinases other than ACE18. This raises the possibility of “ACEi bypass”, wherein ACEi may incompletely or ineffectively suppress angiotensin II receptor signaling, resulting in persistent RAS activity. In contrast, ARB antagonize angiotensin II receptor activity irrespective of the upstream conversion enzyme, potentially leading to more effective RAS inhibition. Such a pharmacologic distinction may result in RAS downregulation from ACEi that is adequate to treat HTN and CKD but insufficient to affect cancer growth, whereas ARB may provide enough RAS inhibition for all three processes. Alternatively, the disparate findings between ARB and ACEi may be attributable to the baseline differences between patients taking these two classes of medications.
The advantages with ARB were only observed relative to patients with CKD or HTN and not relative to those without these diagnoses. This finding seems consistent with the working theory that pathologic upregulation of RAS, as occurs in CKD19 or HTN20, contributes to oncogenesis, and that antagonizing RAS abrogates this effect. ARB may therefore convert the pathologic RAS activity in patients with CKD or HTN to the physiologic RAS activity of patients without them. This normalization of RAS signaling may reverse the theorized oncogenic effect.
It is also possible that ARB may exert an anticancer effect in HNC patients who have normal systemic RAS activity but whose tumors have co-opted RAS signaling for oncogenesis. In this case, our study may have simply been underpowered to detect a significant difference between nD and D+ARB. The multivariable HRs for OS and CSS of 1.09 and 1.11, respectively, directionally favor the ARB group but do not attain the prespecified threshold for statistical significance. It is therefore conceivable that with more patients and an attendant increase in power, a significant difference would have been observed in favor of patients taking ARB. This observation would be provocative in light of the adverse prognosis conferred by DM or CKD and would justify further study of ARB as therapeutic adjuncts in HNC patients without these comorbidities.
RAS inhibition has already generated considerable interest in gastrointestinal oncology. A recently published single-arm phase II trial incorporating the ARB losartan into neoadjuvant therapy for locally-advanced pancreatic cancer demonstrated unprecedented margin-negative resection rates21. Losartan is now being evaluated in a randomized phase II study of multimodality therapy for borderline and locally-advanced pancreatic cancer (NCT03563248).
As yet, there are no active or completed clinical trials evaluating RAS inhibitors in HNC; however, our study of American patients, coupled with the aforementioned Taiwanese experience8, suggests ARB may be efficacious in this disease. Nevertheless, any benefit must be balanced against potential toxicity. A Japanese study of 305 patients undergoing chemoradiotherapy for HNC found no association of ACEi/ARB with aspiration pneumonia22. Conversely, two studies found an increased risk of acute kidney injury (AKI) among HNC patients undergoing chemoradiotherapy and taking RAS inhibitors23,24. Importantly however, increases in serum creatinine, which both analyses used to define AKI, are a common effect of RAS inhibition and typically indicate preservation of renal function25. This means it is not clear how much of the observed increases in creatinine among patients taking ACEi/ARB actually reflect physiologic insult to the kidney and confounds interpretation of increases in serum creatinine. Ultimately, while the specific toxicity profile of ACEi/ARB in HNC remains to be defined, these remain some of the most widely prescribed medications in the United States26 and are well-tolerated by a majority of users. They are also broadly available in generic formulations and as a result tend to be less expensive than interventions approved expressly for cancer. On balance, the minimal symptom and financial toxicity associated with ACEi/ARB therapy mean that virtually any amount of clinical efficacy in HNC would translate to a favorable cost-benefit ratio at both patient and system levels.
Limitations inherent to SEER-Medicare are applicable to our analysis. First, as a retrospective study, our analysis is vulnerable to selection bias, and unmeasured or inadequately controlled confounders may have influenced our findings. Furthermore, large datasets may be vulnerable to misclassification bias and incomplete ascertainment of data, which can compromise the integrity of findings. Next, key prognostic factors such as performance status, HPV status, tobacco or alcohol abuse, and adverse pathologic features are unavailable in the dataset and may have been imbalanced between disease/drug groups. Third, SEER-Medicare includes only patients eligible for Medicare (generally ages 65 and up), and only patients enrolled on fee-for-service Medicare were included in this analysis, leading to the exclusion of a large portion of patients initially considered for inclusion and potentially limiting the external generalizability of our results. This means that our findings may not be applicable to patients living outside geographic areas covered by SEER registries, those ineligible for Medicare, or those who do not have continuous coverage in fee-for-service Medicare. Finally, oncologic endpoints available in the dataset are limited to survival and cause of death. We are therefore unable to assess disease control, recurrence, or disease-free survival.
Methodological limitations to our analysis include the heterogeneity in clinical characteristics of our patient population; however, subset analysis failed to identify any subgroup for whom disease/ARB status was significantly associated with survival. In addition, analyzing cancer deaths with the Kaplan-Meier method may overestimate the risk of cancer-related mortality as compared to cumulative incidence; however, the magnitude of this overestimate is minimized by censoring at two years.
In summary, this pharmacoepidemiologic study of RAS inhibitors in HNC demonstrated that patients with CKD or HTN taking ARB experienced significant prolongations in CSS and OS as compared to similar patients not taking ARB; however, nonsignificant improvements in CSS and OS were observed as compared to patients without CKD or HTN. ACEi, on the other hand, were associated with no significant differences in survival. These findings support further investigations of ARB in HNC.
Supplementary Material
Funding Support:
Dr. Karam is funded by the NIDCR (R01 DE028529-01, R01 DE028282-01) and receives clinical trial funding from AstraZeneca for work unrelated to this research. This research was supported by the Population Health Shared Resource, University of Colorado Cancer Center Support Grant (P30CA44688).
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