Article Figures & Data
Figures
- Figure 1
Article selection for inclusion.
Tables
Population Intervention Comparison Outcomes Study Design Main concept Primary care practitioners
Primary care patientsCancer risk assessment tool to determine a primary care patient’s individual risk of cancer Standard clinical care Clinicians
Clinical outcomes including appropriate referral behavior
Patterns and accuracy of risk perception
Cancer knowledge
Frequency of use
Acceptability by physicians
Confidence of use by clinicians
Attitudes to the tool
Patients
Patient cancer anxiety/worry
Acceptability by patients
Patient behavior including uptake of secondary referral behavior
Adherence to screening recommendations
Intention to undergo screening
Satisfaction with consultationRandomized controlled trials Synonyms/search terms Primary care
Primary care clinicians
Primary care physicians
Family practice
General practice
GPs
PatientsRisk-assessment tool
Clinical tool
Risk-prediction tool
Decision-support tool
Risk-assessment model
Computer decision-support tool
Adult population
Cancer
Family history [and synonyms for family]Standard care
Usual careAcceptability
Effectiveness
Frequency of use
Referral data
Appropriateness of management
Risk accuracy
Patient risk perception
Psychosocial outcomes
Cancer worry
Patient behavior– GP = general practitioner; PRISMA = Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
- Table 2
Characteristics of Trials of Cancer Risk Assessment Tools in Primary Care (N = 11)
Author, Year, Risk Tool, Setting Disease(s) Sample Study Design Intervention(s) Overall Risk of Biasa Schroy et al22 2011
Your Disease Risk
United StatesCRC 665 patients (223 combined intervention; 212 decision aid alone; 231 control)
50 clinicians (47 general internists; 3 nurse practitioners)
2 clinicsRCT (3 groups)
Patients randomized before routine visit with primary care clinicianControl: usual care and generic lifestyle change advice for disease prevention
Intervention 1: decision aid for CRC screening
Intervention 2: decision aid for CRC screening plus CRC personalized risk assessmentLow/unclear Schroy et al23 2012
Your Disease Risk
United StatesCRC 825 patients (280 combined intervention; 269 decision aid alone; 276 control)
61 clinicians (47 general internists; 11 family physicians; 3 nurse practitioners)
2 clinicsRCT (3 groups)
Patients randomized before routine visit with primary care clinicianControl: usual care and generic lifestyle change advice for disease prevention
Intervention 1: decision aid for CRC screening
Intervention 2: decision aid for CRC screening plus CRC personalized risk assessmentLow/unclear Rubinstein et al24 2011
Family Healthware Impact Trial (1)
United StatesCRC, BC, and OC,b heart disease, stroke, and diabetes 3,283 patients (2,077 intervention; 1,206 control)
41 clinics (23 intervention; 18 control)Cluster RCT
Cluster randomization at clinic levelControl: standard print messages about screening and lifestyle choices recommended for general health
Intervention: patient self-completed risk assessment using the Family Healthware risk assessment tool; personalized risk prevention messages tailored to familial riskUnclear Ruffin et al25 2011
Family Healthware Impact Trial (2)
United StatesCRC, BC, and OC,b heart disease, stroke, and diabetes 3,344 patients (2,105 intervention; 1,239 control)
41 clinics (23 intervention; 18 control)Cluster RCT
Cluster randomization at clinic levelControl: standard print messages about screening and lifestyle choices recommended for general health
Intervention: patient self-completed risk assessment using the Family Healthware risk assessment tool; personalized risk prevention messages tailored to familial riskUnclear Wang et al26 2012
Family Healthware Impact Trial (3)
United StatesCRC, BC, and OC,b heart disease, stroke, and diabetes 3,344 patients (2,105 intervention; 1,239 control)
41 clinics (23 intervention; 18 control)Cluster RCT
Cluster randomization at clinic levelControl: standard print messages about screening and lifestyle choices recommended for general health
Intervention: patient self-completed risk assessment using the Family Healthware risk assessment tool; personalized risk prevention messages tailored to familial riskUnclear Emery et al27 2007
GRAIDS Trial EnglandCRC, BC, and OCb 240 patients received GRAIDS intervention; 84 referred to cancer genetics clinic from control practices
45 clinics (23 intervention; 22 control)Cluster RCT
Cluster randomization at clinic levelControl: 45-minute presentation to all GPs in practice on cancer genetics and copy of referral guidelines for cancer genetics clinic
Intervention: 45-minute presentation on cancer genetics to all GPs in practice and copy of referral guidelines for cancer genetics clinic; 1–2 “lead clinicians” per practice trained to use web-based GRAIDS risk assessment tool for OC, CRC, and BCLow Campbell et al28 1997
Health risk survey
AustraliaCervical cancer 679 female patients (354 intervention; 325 control)
2 clinicsRCT
Randomization at patient levelControl: patient self-completed health risk survey
Intervention: patient self-completed health risk survey and was given summary including eligibility for cervical screening and date of last Pap testLow/unclear Wilson et al29 2006
Risk assessment checklist
ScotlandBC 346 clinicians (230 intervention; 116 control)
86 clinics (57 intervention; 29 control)Cluster RCT (2:1)
Randomization at clinic levelControl: standard Scottish guidelines to assess risk for referral to cancer genetics sent to GPs
Intervention: multifaceted intervention including risk assessment checklist for CRC, BC, and OC; information about cancer genetics; patient information booklets; web links cancer/genetics; e-mail link to cancer genetics services; referral letter proforma; education sessions about cancer geneticsLow Emmons et al30 2004
Harvard Colorectal Cancer Risk Assessment Tool
United StatesCRC 353 patients (134 absolute risk only; 146 absolute plus relative risk; 73 control)
2 clinicsRCT
Randomization at patient levelAll participants used the Harvard Colorectal Cancer Risk Assessment Tool
Control: patients received passive risk communication without risk presentation
Intervention: patient risk tool providing 4 different combinations of presentations of risk: (1) absolute and relative risk, (2) absolute risk only, (3) absolute and relative risk with the ability to manipulate the risk input to change the output, and (4) same as for (3) but absolute risk onlyLow Weinstein et al31 2004
Harvard Colorectal Cancer Risk Assessment Tool
United StatesCRC 353 patients (134 absolute risk only; 146 absolute plus relative risk; 73 control)
2 clinicsRCT
Randomization at patient levelAll participants used the Harvard Colorectal Cancer Risk Assessment Tool
Control: patients received passive risk communication without risk presentation
Intervention: patient risk tool providing 4 different combinations of presentations of risk: (1) absolute and relative risk, (2) absolute risk only, (3) absolute and relative risk with the ability to manipulate the risk input to change the output, and (4) same as for (3) but absolute risk onlyLow Holloway et al22 2003
Risk assessment scale
WalesCervical cancer 1,890 female patients (772 intervention; 1,118 control)
29 clinics (15 intervention; 14 control)RCT
Randomization at clinic levelControl: no risk assessment
Intervention: practice nurse risk communication package including a paper-based risk assessment scale based on level of education, current smoking status, number of years of oral contraceptive use, and number of sexual partners ever33Low BC = breast cancer; CRC = colorectal cancer; GP = general practitioner; GRAIDS = Genetic Risk Assessment on the Internet with Decision Support; OC = ovarian cancer; Pap = Papanicolaou; RCT = randomized controlled trial.
↵a Bias assessed using the Cochrane Collaboration risk of bias based on: (1) sequence generation; (2) allocation concealment; (3) blinding of participants, personnel, and outcome assessors; (4) assessment of incomplete outcome data; (5) selective outcome reporting; (6) “other” sources of bias not listed. Low risk of bias = low risk of bias across all domains. Unclear risk of bias = unclear risk of bias for 1 or more key domains. High risk of bias = high risk of bias for 1 or more domains.
↵b These trials assessed patients’ risk for BRCA mutation rather than specifically discussing ovarian cancer screening.
Outcomes Evaluated Author, Year Randomization Unit Results Patients Risk perception Wang et al26 2012 Clinic In patients who underestimated their CRC risk, the intervention increased accuracy of risk perception (intervention 17% vs control 10%, P = .05).
There was no increase in accuracy of risk perception between groups in women who underestimated their risk for BC (intervention 18% vs control 14%, P = .4) or OC (intervention 8% vs control 13%, P = .4).Emery et al27 2007 Clinic There was no difference in mean risk perception between patients referred from intervention vs control practices. Nonsignificant trend seen toward more accurate risk perception at the point of referral in intervention patients, with fewer overestimating their risk of cancer (OR = 1.50; 95% CI, 0.62–3.67; P = .36). Holloway et al32 2003 Clinic There was no change in risk perception of cervical cancer between groups (OR = 1.07; 95% CI, 0.85–1.35). Emmons et al30 Weinstein et al31
2004Patient Accuracy of risk perception increased if risk was presented as combined relative and absolute risks or as absolute risk only vs control (for both people who overestimated and who underestimated their isk preintervention). Screening intentiona Holloway et al32 2003 Clinic Women at intervention clinics were more likely to intend to reduce their screening interval for cervical screening in line with national guidelines (intervention 44% vs control 61%; OR = 0.51; 95% CI, 0.41–0.64; P <.001). Schroy et al22 2011 Patient Mean intention scores to schedule a CRC screening test were higher for both intervention groups vs the control group: intervention group 1: DA (mean = 4.4; SD = 1.0); intervention group 2: DA+YDR (mean = 4.3; SD = 1.0); control group (mean = 3.9; SD = 1.4) (P <.001).
Mean intention scores to complete a CRC screening test were higher for both intervention groups vs the control: intervention group 1: DA (mean = 4.3; SD = 1.0); intervention group 2: DA+YDR (mean = 4.3; SD = 1.0); control group (mean = 3.9; SD = 1.3) (P <.001).Schroy et al23 2012 Patient Booking a screening test:
DA group was more likely to book a CRC screening test than control group at 1 month (69.1% vs 60.5%, P <.035); 3 months (71.8% vs 62.3%, P = .019); 6 months (77.0% vs 65.2%, P = .002); and 12 months (80.7% vs 71.4%, P = .011).
DA group was more likely than DA+YDR group to book a CRC screening test at 1 month (69.1% vs 60.4%, P <.031); 6 months (77.0% vs 67.1%, P <.010); and 12 months (80.7% vs 73.6%, P = .048).Screening adherenceb Rubinstein et al24 2011 Clinic CRC screening increased in both groups over time: intervention, from 76% to 84%, and control, from 77% to 84% (P = .95).
BC screening increased in both groups over time: intervention, from 73% to 82%, and control, from 78% to 85% (P = .82).
No difference between intervention and control groups in screening adherence for CRC, BC, or OC (P >.09) after 6 months.Holloway et al32 2003 Clinic No difference in actual cervical screening intervals and consistency with guidelines between groups at 5 years: intervention 5%, control 7% (OR = 0.61; 95% CI, 0.36–1.03; P = .063). Schroy et al23 2012 Patient Completing a CRC screening test:
DA group was more likely than control group to complete test (43.1% vs 4.8%, P = .046)Campbell et al28 1997 Patient No difference in cervical screening in women identified as being “underscreened” (P >.05). Behavior change Ruffin et al25 2011 Clinic Intervention group was more likely than control group to increase daily fruit and vegetable intake from ≤5 servings to ≥5 servings (OR = 1.29; 95% CI, 1.05–1.58) and to increase physical activity to 5–6 times/week for ≥30 minutes per day (OR = 1.47; 95% CI, 1.08–1.98). Anxiety/worry Emery et al27 2007 Clinic Cancer worry was lower in patients referred from intervention practices vs from control practices: mean difference = −1.44 (95% CI, −2.64 to 0.23; P = .02). Holloway et al32 2003 Clinic Women at intervention practices were less likely to be “fearful of cervical cancer” (OR = 0.66; 95% CI, 0.47–0.93; P = .019), “concerned about chances of serious problems with a smear in the future” (OR = 0.70; 95% CI, 0.51–0.95; P = .026), and “anxious about a recent smear test” (OR = 0.81; 95% CI, 0.66–0.98; P = .036).
No differences seen between women at intervention vs control practices in “concern about their smear result” (OR = 0.75; 95% CI, 0.45–1.24; P = .25).Emmons et al30 Weinstein et al31 2004 Patient 33% of all participants in the study had less cancer worry and 17% had more cancer worry after using the Harvard CRC Risk Tool (comparative data between groups not reported). Knowledge Emery et al27 2007 Clinic There was a nonsignificant increase in cancer knowledge in patients referred from intervention practices vs from control practices: BC knowledge mean difference = 0.11 (95% CI, −1.05 to 1.27) and CRC knowledge mean difference = 0.64 (95% CI, −1.01 to 2.29). Wilson et al29 2006 Clinic No difference seen in patient knowledge between groups for items “Stress is a major cause of BC” (23% vs 23%, P = .98); “Having one close relative with BC always increases your risk considerably” (88% vs 91%, P = .71); and “Minor injury to the breast can cause BC” (20% vs 23%, P = .78). Holloway et al32 2003 Clinic 85% of women at control practices incorrectly agreed that “cervical cancer is among the top 4 female cancers in the UK” compared with 22% of women at intervention practices (OR = 0.05; 95% CI, 0.02–0.11; P <.0001). Schroy et al22 2011 Patient DA groups and DA+YDR group both had increased knowledge scores vs control: intervention group 1 (DA): mean = 3.2; SD = 2.6; intervention group 2 (DA+YDR): mean = 3.0; SD = 2.5; control: mean = 0.8; SD = 2.2 (P <.001).
No differences seen in knowledge scores between DA and DA+YDR groups.Satisfaction Schroy et al22 2011 Patient satisfaction was higher for DA or DA+YDR vs control: intervention group 1 (DA): mean = 50.7; SD = 6.2; intervention group 2 (DA+YDR): mean = 50.5; SD = 6.2; control group: mean = 46.7; SD = 7.9 (P <.001). Satisfaction did not differ between DA and DA+YDR groups. Clinicians Appropriate screening and/or referral Emery et al27 2007 Clinic Increase seen in referral rate to cancer genetics clinic in intervention practices; mean difference = 3.0 referrals per 10,000 patients per practice per year (95% CI, 1.2–4.8; P = .002).
Referrals from intervention practices were more likely to be consistent with referral guidelines and therefore “appropriate” vs control practice referrals (OR = 5.2; 95% CI, 1.7–15.8; P = .006).Wilson et al29 2006 Clinic No difference seen between groups in appropriateness of referrals: intervention 58%, control 48% (RR = 1.18; 95% CI, 0.88–1.37). Clinician confidence Emery et al27 2007 Clinic Clinicians’ confidence in managing people with a family history of cancer increased in intervention practices vs control practices (P <.0001). Wilson et al29 2006 Clinic No change seen in clinician confidence between groups for the following about BC risk: “taking appropriate family history” (60% vs 61%, P = .93); “knowing which patients need to be referred” (40% vs 33%, P = .27); “reassuring low-risk patients” (57% vs 52%, P = .46); and “being able to answer questions” (23% vs 22%, P = .77).
The Article in Brief
Cancer Risk Assessment Tools in Primary Care: A Systematic Review of Randomized Controlled Trials
Jennifer G. Walker , and colleagues
Background Risk assessment tools can be used in primary care to identify those most likely to benefit from tailored prevention efforts. This is the first systematic review of randomized controlled trials implementing cancer risk tools in primary care.
What This Study Found Although cancer risk assessment tools may increase patients' risk perception, knowledge, and screening intentions, they do not necessarily change screening behavior. Overall, use of a tool was greater if initiated by patients, if used by a dedicated clinician, and when combined with decision support. Health promotion messages within the tool demonstrated positive effects on behavior change.
Implications
- The findings suggest that while risk tools may increase actual intentions to have cancer screenings, additional interventions at the clinician or health system level may be needed to increase risk-appropriate cancer screening behavior.
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