Abstract
PURPOSE We conducted this review to identify published randomized controlled trials (RCTs) of cancer risk assessment tools used in primary care and to determine their impact on clinical utility (clinicians), screening uptake (patients), and psychosocial outcomes (patients).
METHODS We searched EMBASE, PubMed and the Cochrane databases for RCTs of cancer risk assessment tools in primary care up to May 2014. Only studies set in primary care, with patients eligible for screening, and English-language articles were included.
RESULTS The review included 11 trials of 7 risk tools. The trials were heterogeneous with respect to type of tool that was used, type(s) of cancer assessed, and outcomes measured. Evidence suggested risk tools improved patient risk perception, knowledge, and screening intentions, but not necessarily screening behavior. Overall, uptake of a tool was greater if initiated by patients, if used by a dedicated clinician, and when combined with decision support. There was no increase in cancer worry. Health promotion messages within the tool had positive effects on behavior change. Trials were limited by low-recruitment uptake, and the heterogeneity of the findings necessitated a narrative review rather than a meta-analysis.
CONCLUSIONS Risk tools may increase intentions to have cancer screening, but additional interventions at the clinician or health system levels may be needed to increase risk-appropriate cancer screening behavior.
INTRODUCTION
Cancer screening programs have been introduced in many countries for breast,1 colorectal,2 and cervical3 cancer. With the growing recognition of the potential harms from population-based cancer screening programs,4 risk-stratified screening is being proposed as a way of reducing harm and focusing on populations at higher risk of cancer. This concept can also be applied to primary preventive measures, especially as the evidence to support chemoprevention for common cancers such as breast and colorectal builds.5,6 If risk-stratified cancer prevention is to be implemented, it requires risk assessment tools that can be used in primary care to identify those most likely to benefit from tailored prevention.7
Cancer risk prediction models, based on epidemiologic data, calculate an individual’s likelihood of developing cancer, identify an individual’s risk of carrying a genetic mutation for a specific cancer (eg, BRCA 1 or BRCA 2), or both.8,9 Newer risk models are beginning to incorporate genomic profiles and environmental exposures,10 a trend that is likely to grow with the movement toward precision medicine.11 Risk assessment tools facilitate the translation of these risk models to estimate an individual’s likelihood of developing different cancers by assessing the combination of risk factors including genetic, environmental12,13 and behavioral12 risk factors. Examples include the US National Cancer Institute (NCI) colorectal cancer risk tool,14 which incorporates the risk model developed by Freedman et al15; the NCI breast cancer risk tool, which applies the Gail breast cancer risk prediction model16; and MelaPRO for assessing risk of melanoma.17
Primary care has an important role in the delivery of cancer screening programs and can increase screening uptake.18 Successful implementation of risk assessment tools into primary care is needed if risk-stratified cancer prevention and the promises of precision medicine are to be achieved.
In this article, we report the first systematic review of randomized controlled trials (RCTs) that have tested cancer risk tools in primary care. The review specifically investigated measures of clinical utility such as clinician referrals and patient cancer screening behaviors, as well as psychosocial outcomes.
METHODS
This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Table 1)19 and is registered with Prospero (registration number: CRD42014008892).20
The Systematic Review Question Design According to the PRISMA Guidelines19
We searched the PubMed, EMBASE, and Cochrane databases for English-language articles published up to May 2014, focusing on search terms based on the concepts of “risk assessment tools,” “cancer,” “primary care,” and outcomes such as “cancer worry,” “risk perception,” “clinician confidence,” “referral behavior,” and “screening behavior.” Additional articles were identified through citation tracking and reference checking.
Eligibility Criteria
Studies were ineligible if they involved tools that did not estimate cancer risk, assessed prognostic tools for patients with an existing cancer diagnosis, were not implemented in a primary care setting, or did not evaluate the tool using RCTs (Figure 1).
Article selection for inclusion.
The populations studied included primary care clinicians (general practitioners, family physicians, and community medicine clinicians) and patients of primary care clinicians, as long as they were adults without an existing (known) cancer diagnosis (Table 1).
Study Appraisal and Synthesis Methods
The primary author (J.W.) assessed all citation abstracts, which were reviewed by a second author (M.P.). Two other researchers (P.P.C.C., S.L.) assessed full-text articles. Data were extracted and studies were critically appraised for bias by 3 reviewers (J.W., P.P.C.C., S.L.) using the Cochrane Collaboration’s tool for assessing risk of bias21 (Table 2).22–31
Characteristics of Trials of Cancer Risk Assessment Tools in Primary Care (N = 11)
The heterogeneity of interventions and outcomes precluded any meta-analysis of the data. The review provides a narrative synthesis of the data.
RESULTS
Study Selection
Our database searches identified 989 studies. After title and abstract review, and removal of 37 duplicates, 210 full-text articles were assessed for eligibility. Eleven articles reporting trials of 7 risk tools were included (Table 1 and Figure 1).
Study Characteristics
The review included trials of risk assessment tools that were either completed by clinicians with patients or self-completed by patients. Risk tools included web-based risk tools, paper-based risk checklists, and multifaceted interventions involving patient resources, clinician education, or both. The studies included a wide range of outcomes and cancers (Table 2).
The trials varied in their design, including the unit of randomization (clinic or patient) and the population testing the intervention (clinician or patient). Of the 11 studies, 3 randomized by clinic and trialed a clinician-targeted intervention,27,29,32 3 randomized by clinic and trialed a patient-targeted intervention,24–26 and 5 randomized by patient and trialed a patient-targeted intervention.22,23,28,30,31 One study randomized patients by clinic days to reduce potential contamination.28 We examined the unit of randomization as a possible source of heterogeneity of the results and found no clear trends (Table 3).
Results of Trials of Cancer Risk Assessment Tools in Primary Care
Recruitment proportions of eligible study participants varied from very low (14% to 25%)24–26,30,31 to very high (93% to 95%).28,32 Contacting eligible patients by mail and following them up with a telephone call yielded a low recruitment. 24–26,30,31 More successful recruiting (93% to 95% of eligible participants) was achieved with a dedicated research assistant or practice nurse recruiting eligible patients in the primary care waiting room before their appointment.28,32 Similarly, when the intervention was delivered by a practice nurse, 75% of patients completed a risk assessment,28 but when clinicians were required to complete training, engagement was low (12% of intervention general practitioners attended).29
Outcomes
Study outcomes are shown in Table 3 and discussed in detail below.
Accuracy of Patient Risk Perception
Overall, there was limited evidence that risk assessment tools altered patients’ risk perception, except in specific subgroups. For example, in the Family Healthware Impact trial,26 there was a significant increase in accuracy of risk perception in those patients who underestimated their risk of colorectal cancer at baseline, but not in women who underestimated their risk of breast cancer. The trial of the Harvard Colorectal Cancer Risk Assessment Tool specifically tested different risk presentation formats. In people who either underestimated or overestimated their risk at baseline, accuracy of risk perception was improved by either absolute risk alone or absolute risk plus relative risk formats, compared with the control patients.26,30,31 The Genetic Risk Assessment on the Internet with Decision Support (GRAIDS) trial and a trial assessing cervical cancer risk found no significant differences in risk accuracy for colorectal cancer,27 breast cancer,27 or cervical cancer.32
Patient Behaviors
Four trials explored screening behavior outcomes, including screening intentions, patient booking/planning a screening test, and patient completing a screening test.
Schroy et al22 tested a pair of interventions. Intervention 1 was a shared decision-making tool, and intervention 2 was a combined shared decision-making tool plus a risk assessment tool (Your Disease Risk), comparing them both with usual care. Immediately postintervention, intentions to order a screening test and intentions to complete a screening test were higher in both intervention groups relative to the control group (P <.001) with no difference between the 2 interventions. During the 12-month follow-up, participants using the decision aid alone (intervention 1) were more likely at every time point to book a test than the control group, and similarly, the decision aid increased the likelihood of completing a screening test when used alone, but not when combined with risk assessment.23
In the Family Healthware Impact trial, there was an increase in colorectal cancer and breast cancer screening in both groups, but no difference in screening rates between the intervention and control groups at 6 months. Of further note, the relatively high rates of cancer screening at baseline in both groups suggested a ceiling effect.24
Holloway et al32 trialed the effect of a risk tool on reducing time intervals between cervical screening, which, at the time of the trial in the United Kingdom, was recommended every 5 years. In the short term, women in the intervention group intended to have screening less frequently, but at 5 years of follow-up, there was no significant difference.
In contrast, Campbell et al28 tested a risk tool with women in primary care in Australia to identify underscreened women and encourage them to have risk-based cervical screening. At 6 months of follow-up, women in the intervention group were no more likely to have had a cervical screening test than those in the control group.
The Family Healthware Impact trial also assessed impact on lifestyle behaviors.25 The risk tool provided age-specific and sex-specific health messages to participants based on their family history of heart disease, stroke, diabetes, colorectal cancer, breast cancer, and ovarian cancer. After 6 months, participants in the intervention group were significantly more likely to have increased their daily fruit and vegetable intake, and their physical activity.
Patient Cancer Worry
None of the 3 trials that measured cancer-related anxiety found any increase after risk assessment. The GRAIDS trial recruited patients who had discussed concerns about their familial cancer risk with their general practitioner.27 Patients referred to cancer genetics services from practices that used the GRAIDS tool had a lower cancer worry than patients referred from the control practices. In the cervical screening trial of Holloway et al,32 women receiving the intervention were less likely to be “fearful” of cervical cancer, less “concerned about chances of serious problems with a smear in the future,” and less “anxious about a recent smear test.”
In the trial of the Harvard Cancer Risk Assessment and Communication Tool, 33% of participants reported feeling less worried about getting colorectal cancer, but 17% reported increased worry about the disease after using the tool.30,31 These associations were seen regardless of whether the risk was presented as absolute risk, relative risk, or combined risk. There were no comparable control data in this trial for cancer worry.
Patient Knowledge
Patient knowledge was measured by understanding of population cancer risk, causes of cancer, and screening guidelines. Schroy et al22 found that both intervention groups had improvements in their knowledge of colorectal cancer screening guidelines, rationale, and goals. Women in the cervical screening trial had a greater understanding of screening guidelines and, in particular, screening intervals recommended for cervical screening as a result of the intervention.32 Wilson et al29 found no differences in patient knowledge between groups despite patient and clinician education.
Patient Satisfaction
Only 1 study measured patient satisfaction. In this study, the use of a decision aid with or without a risk tool improved patient satisfaction with making screening decisions compared with the control condition.22
Appropriate Clinician Referrals, Screening, or Both
Two trials from the United Kingdom looked at the effect of risk tools on “appropriateness of referrals” to cancer genetics services by comparing them against local referral guidelines.27,29 In the GRAIDS trial, risk assessment increased the proportion of appropriate referrals when compared with local guidelines that were implemented with the GRAIDS tool.29 Although there was an increase in appropriate referrals based on the local guidelines, the actual proportion of patients found to be at high risk was no different after more detailed assessment at the genetics clinic. This finding suggests a lack of specificity of the referral guideline that is likely to be implemented more systematically using a risk tool.
DISCUSSION
This systematic review identified only 11 articles reporting trials of 7 cancer risk assessment tools in primary care. Overall, this sample represents a relatively small evidence base, especially in the context of the growing number of cancer risk tools available online. The findings suggest potentially beneficial effects of cancer risk assessment tools in terms of improving accuracy of patient risk perception and knowledge, intentions to have cancer screening, and changes in diet and physical activity, without causing an increase in cancer-specific anxiety. Effects on actual cancer-screening behaviors are less clear. Cancer risk assessment tools may also improve clinician confidence and appropriateness of referrals to cancer genetics services, although the evidence for this benefit is somewhat contradictory from only 2 trials. Risk tools were more successful when they were initiated by patient who were concerned about their family history (of cancer),27 were used by a dedicated clinician,27,32 included health promotion messages,25 and included decision support within the tool.23 Interventions were less successful when tested in trials that involved a passive system for using the risk assessment tool.29
There are some important caveats. The trials included in this review were heterogeneous in terms of the precise nature of the intervention, the unit of randomization, how they were implemented, and the health care setting in which they were studied. Furthermore, some of the populations in which the tools were used were selected toward a group who had existing concerns about their risk, especially about their family history. For example, the relatively low recruitment rates in the US Family Healthware Impact trial probably were associated with response bias toward a well-educated sample with relatively high baseline rates of cancer screening. Additional methodologic weaknesses in some studies included small sample sizes and therefore potentially underpowered trials,28,30,31 poor recruitment rates22–24,26,29–31 lack of clinician engagement in the intervention,29 and patient-reported outcomes that may be influenced by social desirability bias.28 The unit of randomization was not a clear source of heterogeneity despite greater risk of contamination in the patient-randomized trials.
Previous systematic reviews have examined the effect of patient-oriented decision aids in screening33 and also communication of risks in screening programs.34 Our review differs in terms of the nature of the interventions and the populations studied, although the findings are consistent: communication of risks is associated with increased intention to screen, and patient-oriented decision aids can increase knowledge. Two of the included studies examined different methods of communicating risk. The way risks were presented across all trials varied, and none complied with current perceived best practice in presenting risk information as recommended by the International Patient Decisions Aid Standards.35,36
If we are to move toward risk-stratified cancer screening, primary care clinicians will require simple tools to implement validated risk models, which are likely to incorporate genomic as well as lifestyle factors. As the GRAIDS trial demonstrated, risk tools are only as effective as the underlying risk model. Ideally, tools will be able to present absolute risks and the predicted effects of behavior change or chemoprevention on an individual’s risk of cancer. Importantly, they need to be designed to present evidence in ways that highlight the risks of overscreening people at average or low risk as well as the benefit of screening in populations who are most likely to benefit.37 Most of the trials to date have focused on a single cancer or those for which predictive genetic testing was relevant. Validated risk prediction models, however, exist for many common cancers that could ideally be incorporated into a single tool.
In conclusion, despite the existence of many cancer risk assessment tools, there is relatively limited evidence from RCTs of their effectiveness, especially in terms of their impact on risk-appropriate cancer screening behaviors. Risk tools may increase actual intentions to have cancer screening, but additional interventions at the clinician or system level may be needed to increase screening behavior. The results support the use of dedicated staff to maximize implementation of the intervention. The incorporation of health economic evaluation to determine the most cost-effective approaches to delivering risk-stratified cancer screening in primary care, and the potential added cost-benefit of genomic profiling within these trials, will be important outcomes to measure in future trials.
Footnotes
Conflicts of interest: authors report none.
Funding support: This work was supported by funding from the Victorian Comprehensive Cancer Centre, and the National Health and Medical Research Council of Australia (APP1042021).
- Received for publication February 17, 2015.
- Revision received May 14, 2015.
- Accepted for publication June 9, 2015.
- © 2015 Annals of Family Medicine, Inc.
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