Preventive Services Utilization Among Cancer Survivors Compared to Cancer-free Controls

1. INTRODUCTION

Over the last decades, the number of patients surviving cancer, commonly referred to as cancer survivors, has increased rapidly, reaching approximately 11.9 million US survivors in 2008 [1]. A high prevalence of both acute and chronic medical comorbidities, such as influenza infections, hypertension, or metabolic syndrome, are observed in cancer survivors and may be attributable to treatment side effects and a detrimental lifestyle [2, 3]. A recent literature review has shown that these conditions negatively influence survival of cancer patients [4].

In light of the crucial role of comorbidities in the growing number of cancer survivors, several publications analyzed the utilization of preventive services, such as influenza vaccination, or bone densitometry for early detection of osteoporosis, showing contradicting results: both increased and decreased utilization of preventive services were reported [5, 6].

So far, two systematic reviews examined the utilization of screening services among cancer survivors to detect cancer recurrence or secondary malignancies. A systematic review by Wilkins et al. [7] concluded that cancer survivors were less likely to adopt cancer screening than cancer-free controls. Conversely, a systematic review and meta-analysis by Corkum et al. [8] reported that cancer survivors were screened more frequently for new primary breast, cervical, and colorectal cancers compared to cancer-free controls. However, so far no review has focused on the utilization of preventive services other than cancer screening.

Therefore, the aim of this study was to summarize the evidence on utilization of preventive services in cancer survivors compared to cancer-free controls.

2. METHODS

3. RESULT

3.1. Study Selection and Study Characteristics

PubMed and EMBASE database searches yielded 3740 publications after removal of duplicates. 541 publications were identified after screening of titles and abstracts. Of these, 10 studies fulfilled the prespecified inclusion criteria. A total of 71.564 cancer survivors and 241.683 cancer-free controls were included. One study by McBean et al. [15] reported no differences in utilization of influenza vaccination and bone density testing, but failed to provide multivariable adjusted odds ratios and was therefore excluded from further analyses. Fig. (1) shows the record flow chart of this review.

Table 1 details study characteristics. Of 10 included studies, 2 were cross sectional [16, 17], and 8 were matched case control studies [18, 19, 5, 6, 20-23] Among the latter, 2 matched on comorbidities (scale from 0-2) as one of the matching factors [22, 23].

Four studies ascertained the utilization of preventive services using self-reported data such as questionnaires or interviews [5, 16, 7, 20], 5 used insurance claims data [18, 19, 21-23], and one study utilized medical records [6]. One study was conducted in the United Kingdom [6]; 9 studies were localized in the United States of America.

Table 1.

Author/Year	Country	Type of Cancer	Study Design	Study Population	Preventive Service Ascertainment	Number of Participants	Proportion of Female [%]	Mean Age [years]	Preventive Services	NOS
						Cancer Survivors / Controls
Earle et al. 2003	USA	Breast cancer	Matched case-control	1997-98 SEER*-Medicare	Insurance claims data	5965 / 6062	100% / 100%	78.7 / 78.8	During 1997-1998: Influenza vaccination, cholesterol screening, bone densitometry	8
Earle et al. 2004	USA	Colorectal cancer	Matched case-control	1997-98 SEER-Medicare	Insurance claims data	14884 / 16559	57.6% / 56.7%	79.7 / 79.8	During 1997-1998: Influenza vaccination, cholesterol screening, bone densitometry	8
Duffy et al. 2005	USA	Breast cancer	Matched case-control	MEPS†	Self-reported	85 / 340	100% / 100%	61.7 / 63.2	Within previous year: Influenza vaccination; within previous 5 years: cholesterol screening	5
Snyder et al. 2009	USA	Stage 1-3 Breast cancer	Matched case-control (matched on comorbidities)	SEER-Medicare population	Insurance claims data	23731 / 23396	100% / 100%	75.7 / 75.7	During year 2 past cancer diagnosis: Influenza vaccination, cholesterol screening, bone densitometry	8
Khan et al. 2010	UK	Breast, colorectal, prostate cancer	Matched case-control	GPRD‡	Medical record	29244 / 116,418	Breast: 100% / 100% CRC: 49.5%/49.5% Prostate: 0% / 0%	Breast: 67.7/67.7 CRC: 75.1/75.1 Prostate: 76.9/76.9	Annually: influenza vaccination, every 3 years: Cholesterol testing, bone density scan, blood pressure measurement	6
Fairley et al. 2010	USA	All, except non-melanoma skin cancer	Cross-sectional	2006 Massachusetts BRFSS§ survey data	Self-reported	716 / 7375	62.1% / 52.4%	median <64 / <54	Past 12 months: Influenza vaccination	7
Bishop et al. 2010	USA	Leukemic or breast cancer	Matched case-control	CIBTR ǂ	Self-reported	662 / 158	62% / 70%	49.1 / 50.1	Within previous year: Influenza vaccination, blood pressure measurement	7
Snyder et al. 2011	USA	Prostate cancer	Matched  case-control (matched on comorbidities)	2000 SEER-Medicare	Insurance claims data	10482 / 10482	0% / 0%	74.6 / 74.6	During month 49-60 from diagnosis: Influenza vaccination, cholesterol screening,	8
Lowenstein et al. 2015	USA	All, except non-melanoma skin cancer	Cross-sectional	2003 Medicare Current Beneficiary Survey	Self-reported	1882 / 10133	60.6% / 57%	median >75 / <75	Within previous year: Influenza vaccination; within previous 6 months: cholesterol measurement, blood pressure measurement; ever received: bone mineral density, pneumonia vaccination	3
Lafata et al. 2015	USA	Breast, colorectal cancer	Matched case-control	Tumor registries of four non-profit health systems∆	Insurance claims data	5273 / 50759	CRC: 50% Breast: 100%	median <74 / <74	Annually: Lipid profile, bone densitometry for age >65	6

Abbreviations: *SEER: Surveillance, Epidemiology, and End Results Program; † MEPS: Medical Expenditure Panel Survey; ‡GPRD: General Practice Research Database; §BRFSS: Massachusetts Behavioral Risk Factor Surveillance System; ǂ CIBTR: Center for International Blood and Marrow Transplantation; ∆ tumor registries: Group Health Cooperative, Health Alliance Plan/Henry Ford Health System, Kaiser Permanente Colorado and Northwest.

3.2. Preventive Service Utilization

Fig. (2) depicts that, overall, cancer survivors were significantly more likely to utilize preventive services than their cancer-free controls (OR=1.279, 95% CI: 1.145 – 1.430, p<0.001).

Comparably, in separate analyses of each preventive service, cancer survivors were significantly more likely to utilize bone densitometry (pooled OR=1.226, 95% CI: 1.114 – 1.350, p<0.001) and influenza vaccination (pooled OR=1.565, 95% CI: 1.176 – 2.082, p=0.002) than cancer-free controls. No statistically significant difference between cancer survivors and controls was evident for blood pressure measurement and cholesterol/lipid testing (pooled OR=1.322, 95% CI: 0.812 – 2.151, p=0.261; pooled OR=1.046, 95% CI: 0.96 – 1.139, p=0.304).

4. DISCUSSION

This systematic literature review and meta-analysis demonstrates that cancer survivors are more likely to receive certain preventive services than their cancer-free counterparts: The observed pooled estimates were OR=1.23 (95% CI:1.11-1.35, p<0.001) for bone densitometry and OR=1.57 (95% CI: 1.18-2.08, p=0.002) for influenza vaccination. At the same time, no statistically significant difference was evident for cholesterol/lipid tests (OR=1.05, 95% CI: 0.96-1.14, p=0.261) and blood pressure measurement (OR=1.32, 95% CI: 0.81-2.15, p=0.304).

One study matching breast cancer-survivors to cancer-free controls on receipt of mammography supports the results of our review [13]. This may indicate that the utilization of preventive services, such as bone densitometry, is independent from screening for primary malignancies. On an individual study level, only Lafata et al. [21] and Khan et al. [6] reported estimates of less than OR=1 for bone densitometry, blood pressure measurement, and cholesterol/lipid tests. These studies were based on patient populations from the United Kingdom and Non-governmental organization databases, thus indicating that the pooled estimates of this review might not be generalizable to all populations.

For most preventive services, there was considerable to substantial heterogeneity, which was consistently high across subgroups, except for bone densitometry in breast cancer patients.

This heterogeneity is inherent to the outcomes evaluated in the different studies and reflects the inconsistent results reported by earlier reviews on cancer screening services [7, 8]. In our study, heterogeneity might originate from differing timeframes and definitions of preventive services. Further, differences in the study´s underlying patient populations might explain the observed heterogeneity: For example, Synder et al. exclusively included older male patients with prostate cancer [22], while Bishop et al. evaluated predominately younger, female patients with breast cancer or leukemia [20]. On the individual study level, demographics of cancer-survivors and controls were well balanced using matching procedures or multivariable statistical models.

In stratified analyses the pooled estimates showed consistent effects across all subgroups. There was no evidence of effect measure modification, although the tests might be statistically underpowered due to small sample sizes. In sensitivity analyses, the pooled estimates proved robust upon inclusion of one study by Snyder et al. [13]. There was no evidence for publication bias.

Several explanations for differing utilization of preventive and screening services among cancer survivors and their cancer-free counterparts have been suggested, both on the health care provider and individual patient level.

Providers might realize that cancer survivors are at high risk for comorbidities, leading to an increase in examinations. In addition, cancer patients may frequently interact with the health care system. Thus, they might have a higher awareness and eagerness to utilize preventive services. On the contrary, providers may focus on malignancies, ignoring other potential comorbidities. Cancer-survivors may also suffer from their diagnosis emotionally, discouraging further interaction with the health care system [24]. Finally, cancer survivors may face financial challenges due to health-care costs related to cancer treatment, deterring them from further examinations.

Throughout the last decade, recommendations for annual influenza vaccinations have changed in the US. As of 2010, the US Advisory Committee on Immunization Practices recommends influenza vaccinations for all ages [25]. Still, older versions recommend influenza vaccinations only for patients older than 50 years [25]. Since many studies were conducted prior to 2010, one might argue that the observed differences in influenza vaccination arise from an elder population of cancer survivors compared to cancer-free controls. Further, racial and ethnic disparities in US influenza vaccination rates have been reported [26]. Racial/ethnic population imbalances among included studies might explain the observed differences between cancer survivors and cancer-free controls. However, in most of the included studies, cancer survivors and controls were of comparable age and race/ethnicity [5, 6, 18-23]. Since “cancer survivorship” was consistently defined as living after treatment for cancer, it is unlikely that influenza vaccinations given during cancer treatment have biased our results.

In the general population, bone densitometry is routinely utilized as a screening tool for osteoporosis, while in cancer-survivors bone densitometry can be used to detect cancer-treatment related osteoporosis as well: For women undergoing hormone therapy for breast cancer bone densitometry might be utilized to detect treatment related osteoporosis. Most included studies evaluated bone densitometry from medical claims data without reporting on the indication for this preventive service. Therefore, the difference in bone densitometry utilization between breast cancer survivors and cancer-free controls might be biased by diagnostic rather than preventive use. Still, our findings were not limited to this specific subgroup and therefore indicate more generalizable results.

Blood pressure measurement and cholesterol/lipid testing showed non-significant differences between cancer survivors and cancer free controls. In contrast to bone densitometry and influenza vaccination, these preventive services are highly established in general practice and comparably inexpensive [27, 28]. Completion rates of these preventive services are probably much higher, although literature search yielded no explicit US/European rates during the last years. Therefore, the absolute difference in utilization between cancer survivors and controls might be lower in the highly prevalent preventive services blood pressure measurement and cholesterol/lipid testing than for less frequently applied bone densitometry and influenza vaccination. This might contribute to the observed lack of statistical significance in our meta-analysis, aggravated by small sample sizes.

The main limitation of this study is a low sample size and considerable heterogeneity of those studies included, although mitigated to a certain degree by implementation of random effects meta-analyses. Included studies evaluated highly divergent populations such as survivors of prostate, breast or colorectal cancer.

Further, timeframes for preventive services were inconsistent across studies, and often failed to follow national guidelines. Only one study was conducted outside the US, and thus our results might not be generalizable to a broader population or different health care systems. In addition, with only 10 studies included, subgroup analyses were potentially underpowered to detect effect measure modification. Moreover, including only 3 studies evaluating blood pressure measurement limits the interpretability of these results.

The random effects models calculated in this review only estimate one parameter for τ² (between study variability) obtained via the DerSimonian-Laird method. This method neglects potential variability of τ², and thus might provide pooled estimates with confidence intervals too narrow, and p-values too small. Moreover, with random effects models, small studies yield a relatively high weight when compared to large studies, as opposed to fixed effects models. In this review, sample sizes vary from 425 to 145.000 patients, and thus the relatively homogenous weighting of random effects models might be questioned. Finally, only few studies provided separate measures of preventive service utilization distinguishing follow-up care by primary care physicians and oncologists, and subgroup analyses were not feasible [18, 19, 21-23]. It remains unclear, whether the higher preventive service utilization for cancer survivors observed in our study is mainly attributable to specialists´ follow-up.

Still, this review has several strengths. A rigid literature search was conducted, identifying 541 potential publications, of which 10 fulfilled the inclusion criteria. Two authors separately screened and extracted data, thereby minimizing errors. Moreover, statistical analyses and subgroups were chosen a priori.

CONCLUSION

In conclusion, this review demonstrates that cancer-survivors are more likely to utilize the preventive services influenza vaccinations and bone densitometry than their cancer-free counterparts. Our findings must be critically viewed in light of suboptimal screening rates in the general US population, and cancer-survivors in particular [29]. Future research should evaluate the underlying mechanisms, whether results are generalizable to other populations and if utilization of preventive services is translates into prolonged overall survival.

REFERENCES