Abstract
Objective:
To determine whether patient-reported health status, more so than comorbidity, influences treatment in men with localized prostate cancer.
Methods:
Using SEER data linked with Medicare claims and CAHPS surveys, we identified men aged 65–84 diagnosed with localized prostate cancer from 2004–2013 and ascertained their NCI Comorbidity score and patient-reported health status. Adjusting for demographics and cancer risk, we examined the relationship between these measures and treatment for the overall cohort, low risk men aged 65–74, intermediate/high risk men aged 65–74, and men aged 75–84.
Results:
Among 2,724 men, 43.0% rated their overall health as Excellent/Very Good while 62.7% had a comorbidity score of 0. Beyond age and cancer risk, patient-reported health status was significantly associated with treatment. Compared to men reporting Excellent/Very Good health, men in Poor/Fair health less often received treatment (OR 0.71, 95% CI 0.56–0.90). Younger men with intermediate/high risk cancer in Good (OR 0.60, 95% CI 0.41–0.88) or Fair/Poor (OR 0.49 95% CI 0.30–0.79) health less often underwent prostatectomy versus radiation compared to men in Excellent/Very Good health. In contrast, men with NCI comorbidity score of 1 more often received treatment (OR 1.37, 95% CI 1.11–1.70) compared to men with NCI comorbidity score of 0.
Conclusions:
Patient-reported health status drives treatment for prostate cancer in an appropriate direction whereas comorbidity has an inconsistent relationship. Greater understanding of this interplay between subjective and empiric assessments may facilitate more shared decision-making in prostate cancer care.
Keywords: prostate cancer, older adult, health status, patient-reported outcomes
Introduction
Prostate cancer is the most commonly diagnosed non-cutaneous cancer among men in the US.1 Though prostate cancer remains a significant cause of mortality, most men will have an indolent course and will die from an unrelated health condition.2,3 Moreover, curative treatments like radiation and surgery can inflict significant morbidity, particularly for those in poor health, and rarely produce a survival benefit within the first 10 years post-treatment, resulting in net harm for patients.4,5 In fact, in the Prostate Testing for Cancer and Treatment trial, men managed with PSA (prostate specific antigen) monitoring and possible delayed intervention had superior quality of life and equivalent prostate cancer mortality at 10 years.4
Therefore, clinical guidelines advocate for a shared decision-making approach that considers both risks and benefits in conjunction with patient preferences and values.6 While each patient and decision brings unique considerations to bear, evidence generally supports expectant management (e.g., active surveillance, watchful waiting) for low risk prostate cancer and patients with limited life expectancy, such as older men in poor health.7,8 Additionally, age and health status should be considered when considering radical prostatectomy.6 However, past studies have shown an inconsistent relationship between treatment and comorbidity burden—a frequent proxy for patient health, particularly in large population-based studies. Some studies have shown comorbidity to be a major driver of treatment while others have revealed a weak or non-significant relationship.9–13 Across the board though, a substantial number of patients with high comorbidity burden have undergone surgery or radiation, suggesting potential overtreatment.
Accordingly, we hypothesize that patient-reported health status, more so than comorbidity, drives treatment selection for localized prostate cancer. To test this hypothesis, we leverage a novel dataset that enables concurrent measurement of claims-based comorbidity and patient-reported health status. In understanding this dynamic, we can gain a more nuanced understanding of prostate cancer treatment patterns in the US.
Materials and Methods
Data Source, Procedure Assignment, Cohort Identification
We analyzed data from SEER-CAHPS, a database from the National Cancer Institute (NCI), which links Surveillance, Epidemiology, and End Results (SEER) cancer registry cases with Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys and Medicare claims.14 SEER is a population-based cancer registry that maintains data regarding incidence, treatment, and mortality representative of the US population. The Medicare program provides primary health insurance for 97% of the US population aged 65 or older, and successful linkage with Medicare claims is achieved for over 90% of covered patients in SEER.15 Medicare also administers CAHPS surveys annually to a sample of beneficiaries. Within SEER-CAHPS, the average annual survey response rate has been reported to be 71%.14 The CAHPS survey contains questions on demographics, the patient experience, and patient-reported health.
From SEER-CAHPS, we identified men diagnosed with primary prostate cancer from 2004–2013. We identified 3,615 subjects after excluding those diagnosed at death or autopsy (n=47), those who died within 1 month after diagnosis (n=11), those without 6-month continuous enrollment before and after diagnosis except in the case of death (n=318), and those without a CAHPS survey in the 12 months prior to cancer diagnosis (n=89). Next, we restricted our sample to patients aged 65–84 years old (n=3,149) and excluded those with missing patient-reported health measures, missing risk group, or metastatic disease (n=425), creating an analytic cohort of 2,724 (Supplementary Figure 1).
Health Status Measures
We focused on two primary measures of health. First, we abstracted baseline patient-reported health status from CAHPS surveys administered in the 12 months prior to cancer diagnosis. For this survey question, patients rate their overall health using a 5-response scale, which we categorized into 3 groups (i.e., Excellent/Very Good, Good, Fair/Poor). This single-item measure has been shown to be a strong predictor of mortality across multiple populations and specifically for other-cause mortality among men with prostate cancer.8,16
Second, using inpatient and outpatient Medicare claims in the 12 months prior to cancer diagnosis, we calculated comorbidity burden by applying the NCI Comorbidity Index based on the Klabunde modification of the Charlson Comorbidity index and categorized the score as 0, 1, and ≥2.17 A convention of health services research, the Charlson Comorbidity index is a weighted index of 19 conditions associated with 1-year mortality among hospitalized patients.18 Researchers at the NCI (Klabunde et al.) then modified it for use in cancer patients with Medicare claims (e.g., using both hospital and physician claims, excluding cancer-related conditions), which has been shown to be predictive of long-term other-cause mortality among men with prostate cancer.19
Additional Covariates
From SEER we extracted demographics, including age, race/ethnicity, and marital status. We further identified rural/urban status and US region (i.e., Northeast, South, Midwest, and West). As a measure of socioeconomic status, we identified the percentage poverty by census tract (i.e., 0-<5%, 5–10%, 10–20%, 20–100%). Additionally, we collected patient-reported education level (i.e., 8th grade or less, high school graduate or GED, some college or 2-year degree, and 4-year or more college graduate) from CAHPS.
Next, we assigned patients to cancer risk group based on available PSA level, clinical stage, and Gleason Score according to D’Amico risk stratification criteria.20 To simplify risk stratification and maximize sample size, we adopted a binary risk grouping with low risk and intermediate/high risk per D’Amico stratification. While concerns have been raised about the accuracy of PSA in SEER, a recent audit found a significantly lower than predicted error rate and that risk group assignment would be affected in only 0.8% of cases.21
Primary Outcome
For our primary outcome, we dichotomized treatment as any treatment for prostate cancer versus expectant management. We used Healthcare Common Procedure Coding System/International Classification of Diseases, 9th Edition, Clinical Modification codes to define receipt of prostatectomy, radiation, other local therapies (e.g. brachytherapy, cryotherapy), and/or androgen deprivation therapy within 12 months after diagnosis (Supplementary Table 1). Those without any treatment codes for 12 months after diagnosis were assigned to expectant management (i.e., active surveillance or watchful waiting), which has been shown to have both high sensitivity and specificity.22
Statistical Analysis
First, we compared patient characteristics and cancer risk group according to patient-reported health status using chi-squared testing. Additionally, we gave specific attention to the relationship between patient-reported health status and NCI comorbidity score and calculated the pearson correlation.
Next, we fitted multivariable logistic regression models to assess the association between treatment and both NCI comorbidity and patient-reported health status adjusting for patient age, race/ethnicity, marital status, education, census tract poverty level, rural/urban status, US region, and cancer risk group. Thereafter, we examined 3 specific, clinically-relevant subgroups: 1) receipt of any treatment in patients aged 65–74 with low risk disease who would be good candidates for active surveillance; 2) receipt of surgery versus radiation among patients aged 65–74 with intermediate/high risk disease; and 3) receipt of localized treatment (i.e., surgery, radiation, other local therapy) in all patients aged 75–84 who may be suitable for watchful waiting due to limited life expectancy on the basis of their health status or comorbidity burden. Associations with treatment are reported as adjusted odds ratio (OR) with 95% confidence intervals (CI).
This study received exemption from the UNC Institutional Review Board. All statistical testing was completed using computerized software (SAS version 9.4, Cary, NC) with significance level set at p<0.05.
Results
Among 2,724 men with localized prostate cancer, a plurality (43.0%) rated their overall health as Excellent/Very Good, 36.4% as Good, and 20.6% as Poor/Fair. Patient characteristics by patient-reported health status are reported in Table 1. While more men rated their health as Excellent/Very Good than Good or Poor/Fair (except for men aged 80–84), the youngest age group had a higher proportion of men with Poor/Fair health (27.7%, p<0.001). Additionally, race/ethnicity and socioeconomic status were significantly associated with patient-reported health status with better ratings by non-hispanic whites, more educated patients, and those residing in urban or low poverty locations (p<0.001). The relationship between cancer risk group and patient-reported health status did not reach statistical significance (p=0.082).
Table 1.
Patient characteristics according to patient-reported health status.
| Total (%) (N=2,724) | Poor/Fair (%) (N=562) | Good (%) (N=991) | Very Good/Excellent (%) (N=1,171) | P-value | |
|---|---|---|---|---|---|
| Age | <0.001 | ||||
| 65–69 | 444 (16.3) | 123 (21.9) | 148 (14.9) | 173 (14.8) | |
| 70–74 | 1012 (37.2) | 209 (37.2) | 359 (36.2) | 444 (37.9) | |
| 75–79 | 806 (29.6) | 138 (24.6) | 299 (30.2) | 369 (31.5) | |
| 80–84 | 462 (17.0) | 92 (16.4) | 185 (18.7) | 185 (15.8) | |
| Married | 1830 (67.2) | 347 (61.7) | 675 (68.1) | 808 (69.0) | 0.008 |
| Race/Ethnicity | <0.001 | ||||
| Non-Hispanic Whites | 2256 (82.8) | 412 (73.3) | 812 (81.9) | 1032 (88.1) | |
| Black | 272 (10.0) | 102 (18.1) | 100 (10.1) | 70 (6.0) | |
| Other | 196 (7.2) | 48 (8.5) | 79 (8.0) | 69 (5.9) | |
| Setting | <0.001 | ||||
| Rural | 355 (13.0) | 109 (19.4) | 126 (12.7) | 120 (10.2) | |
| Urban | 2369 (87.0) | 453 (80.6) | 865 (87.3) | 1051 (89.8) | |
| Poverty Indicator | <0.001 | ||||
| 0%–<10% | 1398 (51.9) | 219 (39.4) | 496 (50.7) | 683 (58.9) | |
| 10% to <20% | 791 (29.4) | 167 (30.0) | 299 (30.6) | 325 (28.0) | |
| 20% to 100% | 504 (18.7) | 170 (30.6) | 183 (18.7) | 151 (13.0) | |
| Education | <0.001 | ||||
| High school graduate or less | 1220 (46.3) | 347 (63.8) | 473 (49.7) | 400 (35.1) | |
| Some college or 2-year degree | 590 (22.4) | 107 (19.7) | 222 (23.3) | 261 (22.9) | |
| 4-year or more college graduate | 827 (31.4) | 90 (16.5) | 257 (27.0) | 480 (42.1) | |
| Region | <0.001 | ||||
| South | 769 (28.2) | 190 (33.8) | 277 (28.0) | 302 (25.8) | |
| Northeast | 507 (18.6) | 86 (15.3) | 174 (17.6) | 247 (21.1) | |
| Midwest | 292 (10.7) | 63 (11.2) | 112 (11.3) | 117 (10.0) | |
| West | 1156 (42.4) | 223 (39.7) | 428 (43.2) | 505 (43.1) | |
| Risk Group | 0.082 | ||||
| Low | 568 (22.3) | 99 (18.7) | 216 (23.6) | 253 (22.9) | |
| Intermediate/High | 1982 (77.7) | 430 (81.3) | 701 (76.4) | 851 (77.1) | |
| Stage | 0.870 | ||||
| I-II | 2296 (87.4) | 479 (88.4) | 832 (87.3) | 985 (87.1) | |
| III | 330 (12.6) | 63 (11.6) | 121 (12.7) | 146 (12.9) | |
| Prostatectomy | 431 (15.8) | 66 (11.7) | 142 (14.3) | 223 (19.0) | <0.001 |
| Radiation Therapy | 1291 (47.4) | 256 (45.6) | 464 (46.8) | 571 (48.8) | 0.412 |
| Other Local Treatment | 305 (11.2) | 55 (9.8) | 108 (10.9) | 142 (12.1) | 0.328 |
| Androgen Deprivation Therapy | 1024 (37.6) | 237 (42.2) | 373 (37.6) | 414 (35.4) | 0.023 |
| Expectant Management | 687 (25.2) | 156 (27.8) | 247 (24.9) | 284 (24.3) | 0.280 |
Figure 1 shows patient-reported health status according to NCI comorbidity scores. These measures are significantly associated (p<0.001) though weakly correlation (r=0.130). Among patients with NCI comorbidity score of 0, 50.0% rated their health as Excellent/Very Good while 34.5% and 15.5% rated their health as Good or Poor/Fair, respectively. Among patients with NCI comorbidity score of 2 or higher, 25.1% rated their health as Excellent/Very Good with 40.5% as Good and 34.4% as Poor/Fair.
Figure 1. Patient-reported health status according to NCI comorbidity score.
Patient-reported health status and NCI comorbidity score are significantly associated based on chi-squared testing (p<0.001) though weakly correlated based on the Pearson correlation coefficient (r=0.130).
Figure 2 illustrates the relationship between treatment and these measures of health adjusting for patient characteristics and cancer risk group. In the overall cohort, men reporting Poor/Fair health less often received treatment compared to men reporting Excellent/Very Good health (OR 0.71, 95% CI 0.56–0.90). The difference between men with Good vs. Excellent/Very Good health did not reach statistical significance (OR 0.86, 95% CI 0.71–1.05). In contrast, men with NCI comorbidity score of 1 were more likely to receive treatment compared to men with NCI comorbidity of 0 (OR 1.37, 95% CI 1.11–1.70) while the difference between men with NCI comorbidity score ≥2 vs. 0 did not reach statistical significance (OR 1.21, 95% CI 0.95–1.54).
Figure 2. Likelihood of treatment according to patient health.
Adjusted odds ratios for treatment according to patient-reported health status and NCI comorbidity for 4 cohorts: A) any treatment versus expectant management in the overall cohort; B) any treatment versus expectant management for men aged 65–74 with low risk disease; C) surgery versus radiation for men aged 65–74 with intermediate/high risk disease; and D) localized treatment vs. no localized treatment for men aged 75–84. Odds ratios are adjusted for age, race/ethnicity, marital status, education, census tract poverty level, rural/urban status, and US region for all cohorts as well as cancer risk group for cohorts A and D.
These relationships differed by clinical subgroup. Among younger patients with low risk prostate cancer, neither patient-reported health status nor NCI comorbidity score was significantly associated with treatment. Instead, increasing age appeared to contribute nonlinearly to use of expectant management in this subgroup (p<0.05). Among men with intermediate/high risk prostate cancer younger than 75 years old, men with Good (OR 0.60, 95% CI 0.41–0.88) or Fair/Poor (OR 0.49, 95% CI 0.30–0.79) health less often underwent prostatectomy versus radiation compared to men with Excellent/Very Good health. Among men 75–84 years old who could be candidates for watchful waiting depending on their health, patient-reported health status was not significantly associated with receipt of localized treatment. Instead, as in the primary model, men with NCI comorbidity score of 1 more often received localized treatment compared to men with NCI comorbidity score of 0 (OR 1.48, 95% CI 1.09–2.00).
Comment
Treatment choice for prostate cancer remains a highly complicated decision that incorporates a number of data points. In addition to patient preferences and cancer aggressiveness, health status has been identified as a key consideration, which can alter the balance between benefit and harm from treatment. Both in research and in practice, health status has been conceptualized in terms of comorbidity due to its strong relationship with acute and long-term mortality.2,19 However, patient-reported health status has also been shown to be a strong predictor of long-term survival including men with prostate cancer.8,16 Our study found that patient-reported health status predicted treatment in the expected direction (i.e., healthier patients received treatment more often) whereas comorbidity had an inconsistent and at times paradoxical relationship.
Multiple studies have examined the relationship between comorbidity and receipt of treatment in prostate cancer. These studies have been mixed with some demonstrating declining use of treatment with increasing levels of comorbidity and others showing a weak or no significant relationship.9–13 In the Cancer of the Prostate Strategic Urologic Research Endeavor database, investigators found a dose-response relationship between the number of patient-reported comorbidities and likelihood of non-treatment.12 Meanwhile, a study using SEER-Medicare reported a weak relationship between Charlson Comorbidity and non-treatment relative to age while another in the Veterans Affairs population found no relationship between Charlson Comorbidity and expectant management.7,11 When simultaneously accounting for patient-reported health status, our findings show a somewhat unexpected relationship. Patients with NCI comorbidity score of 1 underwent treatment more, not less, than men without comorbidity. Furthermore, this appeared to be concentrated among those aged 75–84 who might otherwise be appropriate candidates for watchful waiting. A similar finding was reported by Pinsky et al. who found in a different cancer database that men with a comorbidity score of 1 were more likely to receive radiation.13 An emerging body of literature in medical decision-making suggests that patients have inherent healthcare seeking preferences. This has been shown to drive cancer testing and offers one plausible explanation for increased treatment use among those with claims indicative of more comorbidity.23,24
In contrast, patient-reported health status appears to be associated with treatment in a manner in line with anticipated risks and benefits. Men with Fair/Poor health—and by extension limited life expectancy—less often underwent treatment for prostate cancer, consistent with current care guidelines.6 Additionally, patient-reported health status appears to be a strong determinant of the type of treatment patients receive. Among younger men with clinically significant prostate cancer, those with Fair/Poor health were half as likely to undergo prostatectomy vs. radiation, perhaps in an effort to minimize the risk of surgical complications and functional morbidity.5 Notably however, despite patient-reported health status being a strong predictor of life expectancy, we did not identify a significant association between patient-reported health status and use of treatment vs. expectant management in younger men with low risk disease or localized treatment in men 75 years old and older who are more likely to die from a competing cause. Rather, age and cancer risk remain the primary drivers of treatment choice, perhaps suggesting further opportunity to refine care based on health status.
This study has several limitations. First, given the retrospective nature of the study, we cannot determine whether the associations we observed influenced physician recommendations for treatment or patient willingness to receive therapy. Second, we are unable to account for the physician’s assessment of relative risks and benefits nor the value judgments, preferences, or biases that give rise to their recommendations, which have been shown to significantly impact counseling and treatment choice.25 Third, this study does not gauge patient preferences, which has been increasingly important in decision-making in prostate cancer. Fourth, the cohort captures cases from 2004–2013 and may not reflect current treatment trends.22 Even so, guidelines at that time acknowledged the significance of health status when deciding between treatment options, a consideration which has not lost relevance despite advances in technology.26 Fifth, the study does not include patients below age 65. However, the role of health status among younger patients is likely to be less given the lower risk of other cause mortality.19 Sixth, due to sample size, the subgroup analyses may lack the power to identify smaller differences in treatment use according to health status. Similarly, we could not pursue other, more granular subgroup analyses, such as the specific relationship between health and treatment among our oldest patients with high risk disease.
These limitations notwithstanding, our findings have potential implications on how to support decision-making in prostate cancer. Current guidelines for prostate cancer treatment recommend shared decision-making, which calls for patients and their providers to discuss treatment options, their risks and benefits, and patient values and preferences and to come to a collaborative decision.6 A key aspect of this process has been an assessment of life expectancy, which has been based on age and recently comorbidity. In fact, several comorbidity-based prediction tools have been developed in an effort to promote better decision-making.17,19 However, their uptake into routine clinical practice has been limited. Instead, increased attention could be given to patient-reported health status and prediction tools based on this single-item health status measure. Already, a predictive nomogram for other-cause mortality among men with prostate cancer has been developed based on this question.14
Furthermore, estimates based on patients’ own perceptions of health may facilitate greater acceptance of this information and incorporation into decision-making. While patients may be amenable to risk-based decision-making when deciding between two effective curative therapies like surgery versus radiation, the choice between treatment versus expectant management for cancer can be more difficult for patients to accept. Ongoing research has found that patients do not view life expectancy as a reason to avoid screening.27,28 Similarly, patients with prostate cancer exhibit a strong desire to be active in their treatment decision-making irrespective of their health status.29 In situations where patients desire treatment despite a low chance for benefit (e.g., surgery for older men with low risk disease), centering the discussion on the patient’s perception of health may lead to a better understanding of their decision-making. This in turn may result in more collaborative discussions that align treatment with risks and benefits, ultimately leading to higher quality of care and patient satisfaction.30
Conclusions
Patient-reported health status appears to be an important determinant in prostate cancer treatment decisions independent of comorbidity. The impact of patient-reported health status was most pronounced when deciding between curative therapies rather than when deciding whether to treat. In contrast, comorbidity had an inconsistent and potentially paradoxical relationship with treatment. Understanding patient perceptions of overall health in the context of their age, cancer risk, and comorbidity burden can contribute to shared decision-making for prostate cancer treatment.
Supplementary Material
Supplementary Figure 1: Cohort flow chart with inclusion/exclusion criteria.
Acknowledgements
Hung-Jui Tan, MD, MSHPM was supported by a Mentored Research Scholar Grant in Applied and Clinical Research, MRSG-18-193-01-CPPB, from the American Cancer Society as well as the NIH Loan Repayment Program. Stephen McMahon was supported by the Carolina Medical Student Research Program from the University of North Carolina, Chapel Hill School of Medicine. These funding sources had no role in the design, conduct, analysis, or decision to publish the manuscript.
The authors have no other financial disclosures or conflicts of interest to report.
This study used the link SEER-CAHPS data resource. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the National Cancer Institute; the Centers for Medicare & Medicaid Services; Information Management Services (IMS), Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-CAHPS data resource.
Footnotes
Declaration of Interests: None
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Associated Data
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Supplementary Materials
Supplementary Figure 1: Cohort flow chart with inclusion/exclusion criteria.