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Systematic Review: Family History in Risk Assessment for Common Diseases FREE

Brenda J. Wilson, BSc, MB, ChB, MSc; Nadeem Qureshi, MBBS, MSc, DM; Pasqualina Santaguida, BSc, PT, PhD; Julian Little, MA, PhD; June C. Carroll, MD; Judith Allanson, MB, ChB; and Parminder Raina, BSc, PhD
[+] Article and Author Information

From the University of Ottawa and Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada; University of Nottingham, Nottingham, United Kingdom; McMaster University Evidence-Based Practice Center and McMaster University, Hamilton, Ontario, Canada; and Mount Sinai Hospital and University of Toronto, Toronto, Ontario, Canada.


Disclaimer: The opinions expressed herein do not necessarily reflect the opinions of the Agency for Healthcare Research and Quality.

Acknowledgment: The authors thank Supriya Janakiraman, Agency for Healthcare Research and Quality Task Officer; Gurvaneet Randhawa; members of the Technical Expert Panel; Alfred Berg, Panel Chair; Wylie Burke; Lisa Madlensky; and Louise Acheson, who were instrumental in defining the parameters of this review. They also thank Lynda Booker, Mary Gauld, Homa Keshavarz, Jinhui Ma, Maureen Rice, Laura Cross-Bardell, and Silvia Visentin for their work in preparing the report and assistance with this manuscript.

Grant Support: By the Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services (contract 290-02-0020).

Potential Conflicts of Interest:Honoraria: B.J. Wilson (McMaster Evidence-based Practice Center), N. Qureshi (McMaster Evidence-based Practice Center), J. Little (McMaster Evidence-based Practice Center), J.C. Carroll (McMaster Evidence-based Practice Center), J. Allanson (McMaster Evidence-based Practice Center).

Requests for Single Reprints: Brenda J. Wilson, BSc, MB, ChB, MSc, University of Ottawa, Department of Epidemiology & Community Medicine, 451 Smyth Road, Ottawa, Ontario K1H 8M5, Canada; e-mail, bwilson@uottawa.ca.

Current Author Addresses: Drs. Wilson and Little: Department of Epidemiology & Community Medicine, University of Ottawa, 451 Smyth Road, Ottawa, Ontario K1H 8M5, Canada.

Dr. Qureshi: University of Nottingham, Institute for Clinical Research, Division of Primary Care, Medical School Queen's Medical Centre, Nottingham NG7 2UH, United Kingdom.

Dr. Carroll: Granovsky Gluskin Family Medicine Centre, 60 Murray Street, 4th Floor Box 25, Toronto, Ontario M5T 3L9, Canada.

Dr. Allanson: Children's Hospital of Eastern Ontario, 401 Smyth Road, Ottawa, Ontario K1H 8L1, Canada.

Drs. Santaguida and Raina: McMaster University Evidence-based Practice Center, DTC, Room 310, 1280 Main Street West, Hamilton, Ontario L8S 4L8, Canada.

Author Contributions: Conception and design: B.J. Wilson, N. Qureshi, P. Santaguida, J. Little, J.C. Carroll, J. Allanson.

Analysis and interpretation of the data: B.J. Wilson, N. Qureshi, P. Santaguida, J. Little, J.C. Carroll.

Drafting of the article: B.J. Wilson, N. Qureshi, P. Santaguida, J. Allanson.

Critical revision of the article for important intellectual content: B.J. Wilson, N. Qureshi, P. Santaguida, J. Little, J.C. Carroll, P. Raina.

Final approval of the article: B.J. Wilson, N. Qureshi, P. Santaguida, J. Little, J.C. Carroll, J. Allanson, P. Raina.

Provision of study materials or patients: P. Santaguida.

Statistical expertise: P. Santaguida, J. Little, P. Raina.

Obtaining of funding: P. Santaguida, P. Raina.

Administrative, technical, or logistic support: P. Santaguida.

Collection and assembly of data: B.J. Wilson, N. Qureshi, P. Santaguida, J. Little, J. Allanson.


Ann Intern Med. 2009;151(12):878-885. doi:10.7326/0000605-200912150-00177
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Family history represents the integration of risk within a family from shared genetic susceptibilities and familial clustering of environmental exposures, lifestyles, and behaviors. Epidemiologic evidence shows associations between family history and risk for many common chronic diseases (17). Thus, family history information might aid in assessing risk for a condition, even in the absence of an understanding of the molecular cause of that condition and even for disorders that do not follow a distinct Mendelian inheritance pattern. Knowledge of family history might also act as a motivator for behavior change (8).

As with any health care intervention, family history–based risk assessment carries resource implications and opportunity costs. We present evidence about the potential beneficial and harmful effects of collecting and using family history information, family history elements that are most useful for risk assessment, and the accuracy of family history information reported by patients. We focus on family history collection and interpretation in a primary care context, in which the population presents a full range of disease risks, primary care practitioners obtain history information, and chronic disease risk assessment and prevention is the goal.

Key Questions

This evidence review addresses 4 of 6 original research questions developed by a panel from the National Human Genome Research Institute and the Office of Medical Applications of Research of the National Institutes of Health. A representative from the panel and the Technical Expert Panel helped refine the scope of the questions and define pertinent eligibility criteria. They recommended focusing on primary care and selecting experimental and quasi-experimental designs for the effectiveness questions.

1. What is the direct evidence that getting a family history will improve health outcomes for the patient or family?

2. What is the direct evidence that getting a family history will result in adverse outcomes for the patient or family?

3. What are the key elements of a family history in a primary care setting for the purposes of risk assessment for common diseases?

4. What is the accuracy of family history, and under what conditions does the accuracy vary?

Data Sources and Selection

We searched for English-language publications in MEDLINE, EMBASE, CINAHL, the Cochrane Central Registry of Controlled Trials, and PsycINFO from 1995 to 2 March 2009. With the exception of question 4, we restricted participants to those who were unselected for high preexisting risk and recruited from general population settings. We excluded studies of patients undergoing genetic testing because of suspicion of high a priori risk. We defined the intervention as the systematic collection of family history by any means, alone or with other risk information. For questions 1 and 2, we restricted study designs to randomized, controlled trials; nonrandomized trials; and before–after studies. For question 3, we restricted designs to retrospective and prospective cohort studies and cross-sectional studies and the conditions of interest to breast, colorectal, ovarian, prostate, and lung cancer; coronary heart disease; stroke; and diabetes. For question 4, we did not restrict study design. The eligible outcomes varied with the research questions. (Full technical report is available at www.ahrq.gov.)

Trained research assistants independently screened each citation using standardized forms and a training manual developed by the reviewers. They assessed eligibility on the basis of title and abstract and retrieved articles if at least 1 judged it potentially eligible. At full-text screening, 2 assistants came to consensus on the identification, selection, and data abstraction. We reviewed all reports with unclear eligibility and resolved any disagreements about selection or data by discussion.

Data Extraction and Quality Assessment

We extracted data on participant characteristics, method of family history collection, study outcomes, study design, and quality. At least 1 reviewer confirmed all data extraction. We assessed quality on the basis of randomization, blinding processes, and completeness of follow-up for controlled trials (9); risk for selection and outcome biases for uncontrolled before–after studies; selection and information biases for longitudinal and cross-sectional analyses relevant to question 3; and spectrum, selection, verification, and masking biases for studies relevant to question 4 (10). For question 4, we treated patient reporting of family history as the index test and the verified disease status of the relatives as the reference test; we assumed that both the index test and the reference test were equivalent across studies.

Data Synthesis and Analysis

We used a descriptive approach to summarize study characteristics and outcomes for all research questions. For question 3, we compared the predictive accuracy of family history elements by first considering specific ancestry, specific relative of interest (for example, mother), degree of relative of interest's relationship to informant (for example, first degree), age of onset of condition in affected relative, and lineage of affected relative (informant's maternal or paternal line) to be categories of family history elements. We then treated any definition of positive family history reported in an article as a combination of these elements. For each report, we noted the elements each definition incorporated. We then calculated the sensitivity and specificity of each definition for predicting or detecting the disease of interest, treating fulfillment of the definition as the test and nonfulfillment as the reference. For each condition, we compared the sensitivities and specificities for each definition (each combination of 1 or more elements).

We decided that meta-analysis was inappropriate because of an insufficient number of studies and data for questions 1 and 2; important clinical heterogeneity across studies and nonindependence of many observations for question 3; and important clinical heterogeneity across studies, insufficient studies for some disease categories, and missing measures of variance for evidence relevant to question 4.

Role of the Funding Source

The Agency for Healthcare Research and Quality, in partnership with the National Institutes of Health Office of Medical Applications of Research Consensus Conferences, suggested the initial questions. The Agency for Healthcare Research and Quality provided copyright release for this manuscript. Both the Agency for Healthcare Research and Quality and the National Institutes of Health Office of Medical Applications of Research representatives were informed of key methodological decisions but did not participate in the literature search, data analysis, or interpretation of the results.

We screened 32 444 titles and abstracts and evaluated 1254 full-text articles. A total of 137 publications met eligibility criteria (Appendix Figure). The Table (1179) summarizes the reviewed studies.

Table Jump PlaceholderTable.  Summary of Reviewed Studies
Evidence That Getting a Family History Improves Outcomes

We identified 2 uncontrolled before–after studies (1112) that evaluated the effect of collecting family history of breast or ovarian cancer with risk personalization on adherence with recommended breast cancer screening behaviors (Appendix Tables 1 and 2). One study was workplace-based (11), and the other recruited walk-in clients of community pharmacies and health fair participants (12). The intervention was telephone-based in 1 study and in-person in the other. The outcomes for both studies were self-reported rates of breast self-examination, clinical breast examination, and screening mammography at 8 (11) or 6 (12) months.

Both studies showed an increase in breast self-examination rates, from 34% to 62% (11) and 31% to 56% (12), and an increase in clinical breast examination rates, from 82% to 92% (P < 0.014) (11) and 86% to 91% (P < 0.090) (12). One study showed an increase in mammography uptake from 76% to 93% (P < 0.057) (11), and the other showed a decrease from 75% to 70% (P < 0.48) (12).

These 2 studies provide limited and insufficient evidence about the effect of collecting family history and personalizing risk on health behavior. They had low statistical power, lacked control groups, and had concurrent co-interventions—such as awareness campaigns—that probably affected results. Also, study participants were from self-selected groups who had relatively high baseline rates of adherence to screening recommendations.

Evidence That Getting a Family History Causes Harm

We identified 1 randomized, controlled trial (13), with 100 randomly assigned and 76 analyzed participants, and 2 uncontrolled before–after studies (1415) (Appendix Tables 3 and 4). Two studies (13, 15) evaluated generic family history assessment, and 1 (14) specifically evaluated cancer history assessment. One study evaluated family history as part of a periodic health examination (13), the second within a dedicated family practice clinic (15), and the third through a special postal survey (14). Personalized risk was provided in person in 2 studies (13, 15) and by letter (low-risk respondents) or in person (high-risk respondents) in the third (14). Anxiety and cancer worry were the reported outcomes.

All 3 studies assessed anxiety by using the short form Spielberger State-Trait Anxiety Inventory (80). The randomized, controlled trial (13) observed an increase in anxiety scores in the intervention group compared with the control group at 1 and 2 weeks after the intervention. However, group scores did not differ 3 months after the intervention (34.15 in the intervention group vs. 34.76 in the control group). Postintervention anxiety scores decreased in 1 uncontrolled study (15) and did not change in the other (14) compared with baseline.

One uncontrolled study (14) observed no overall change in cancer worry (81). Subgroup analyses indicated that high-risk respondents who were subsequently assessed as low risk at specialist assessment had higher postintervention cancer worry scores than the other respondents.

The randomized, controlled trial provides limited evidence that collecting family history and personalizing risk information is not associated with adverse psychological effects at 3 months. The findings of the uncontrolled studies (1415) are consistent with a lack of adverse effects but are undermined by lack of control groups, low participation rates, and possible lack of statistical power. We found considerable heterogeneity in the format of the family history intervention across the 3 studies.

Key Elements of a Family History for Risk Assessment Purposes

We reviewed 20 longitudinal and 21 cross-sectional studies that both reported family history definitions and presented analyzable data for breast cancer (4 studies [1619]), colorectal cancer (3 studies [2022]), prostate cancer (6 studies [2328]), coronary heart disease (8 studies [2936]), stroke (3 studies [3739]), and diabetes (17 studies [4056]) (Appendix Table 5). Forty different definitions of positive family history were used. Few incorporated an age of onset or lineage criteria, and none had an explicit ancestry criterion. The disease frequency in studies ranged from less than 1% to 21%, and the proportion of study participants meeting any given definition of positive family history ranged from 0.3% to 60%. For the longitudinal studies, follow-up ranged from 1 to 20 years.

Sensitivities ranged from 0.01 to 0.51 and specificities from 0.66 to 0.99 across all longitudinal studies and definitions (Appendix Table 6). We observed the highest sensitivities for the definitions “1 or more affected parents” in coronary heart disease, stroke, and diabetes (0.1 to 0.51) and “1 or more affected first-degree relatives” in breast and prostate cancer (0.05 to 0.26). Corresponding specificities were 0.66 to 0.95 and 0.88 to 0.97, respectively. Only “1 or more affected first-degree relatives” was examined for colorectal cancer. Sensitivities ranged from 0.13 to 0.14 and specificity was 0.92.

We observed lower sensitivities for definitions that specified the relative whose status was of interest or required more than 1 relative to be affected.

Sensitivities ranged from 0 to 0.83 and specificities from 0.48 to 1.00 across all cross-sectional studies and definitions. Five studies permitted meaningful within-population comparisons of more than 1 definition (for prostate cancer [27], coronary heart disease [35], and diabetes [41, 50, 53]). Our findings were similar to those for longitudinal studies. The most extensive comparisons were available for diabetes, for which several definitions produced similar sensitivities (“1 or more affected second-degree relatives,” “1 or more affected first-degree relatives or 2 or more affected second-degree relatives,” and “1 or more affected first-degree relatives and 1 or more affected second-degree relatives in same lineage”; “1 or more affected first-degree relatives”; “both parents affected”; and “2 or more affected second-degree relatives from same lineage”). We observed lower sensitivities and higher specificities for definitions that specified the affected relative of interest, required more than 1 relative to be affected, or included an age of onset criterion in the affected relative.

Both the longitudinal and cross-sectional studies showed considerable heterogeneity in underlying disease frequency, proportion of participants who fulfilled criteria for any given definition of positive family history, method of collection, and case definition and ascertainment. Study conclusions are derived from individual studies that compared more than 1 family history definition. For prediction of disease, consistent but weak evidence from the longitudinal studies across different conditions indicates that the highest sensitivities are obtained when definitions focus on disease history in parents or first-degree relatives and that sensitivities decrease with the addition of further required elements. In general, specificities varied inversely with sensitivities. The evidence from the cross-sectional studies is similar for family history as an indicator of prevalent disease, but it is insufficient to draw conclusions because too few comparisons were available.

Accuracy of Family History

Twenty-three studies evaluated the accuracy of reporting family history (Appendix Tables 7 and 8). Informants in these studies had cancer (5772), diabetes (7376), hypertension (7477), or cardiovascular disease (7576, 7879) and were recruited from clinics, disease registries, or population cohort studies (7576). In the case–control studies, unaffected participants (57, 6164, 66, 70, 78) were recruited from the community or identified through administrative databases. Family history was collected in face-to-face interviews (57, 61, 63, 65, 69, 72, 74, 76, 78), mailed surveys (58, 60, 62, 64, 68, 71, 75), or telephone interviews (59, 67, 70, 73). One study (69) did not report the mode of collection. Most reports did not provide detailed information on the type or extent of family history questioning, except for the type of relative of interest. Relatives' actual disease status was verified by using medical records, disease or death registries, or personal contact. Many studies used more than 1 verification method.

Four studies (61, 63, 66, 70) examined reporting of any type of cancer or any type of heart disease (78) in relatives; 2 longitudinal studies (7576) evaluated cohorts with varying prevalence of diseases (hypertension, diabetes, cardiovascular disease, stroke, and asthma). The remaining studies each examined family history of a condition with which the informant was also affected. For reporting of family history of cancer, we observed specificities (correct reporting of absence of disease in relatives) of 0.91 to 1.00. The sensitivities (correct reporting of presence of disease in relatives) were generally more variable and had wider CIs. The ranges differed by type of cancer (breast, 0.72 to 0.95; colon, 0.33 to 0.90; ovarian, 0.42 to 0.83; and prostate, 0.47 to 0.79). For family history of diabetes, hypertension, and cardiovascular disease, most studies showed sensitivities in the range 0.18 to 0.89, with somewhat higher specificities (0.76 to 0.98). Two studies showed higher sensitivities for reporting family history of hypertension (74) and cardiovascular disease (78).

Six of 8 case–control studies (61, 6364, 66, 70, 78) allowed direct comparison of reporting accuracy between affected and unaffected informants. We observed similar specificity for case patients and control participants across all studies but variable sensitivity, with no clear pattern by disease. One longitudinal study (76) showed no effect of participant risk factors on accuracy, whereas a second study (75) showed that probands with disease were less accurate.

We observed no clear association between accuracy and informant age (57, 6163, 6668, 70, 76), sex (6163, 6768, 70, 76), or education level (6163, 6768, 70). Four studies (5960, 63, 68, 73) showed consistently lower accuracy of reported disease history in second- and third-degree relatives.

Most of the studies that evaluated accuracy of family history reporting related to cancer. They provide fair but consistent evidence that informants are better at correctly reporting absence of disease in relatives (specificity) than history of disease (sensitivity). The samples studied were generally highly selected and were not typical of primary care (spectrum bias). In some studies, investigators used different methods to verify the relatives' status (verification bias) and did not apply them consistently. In some studies, the verification of relatives' status may have been done with the knowledge of the reported family history (blinding bias). All of these biases may lead to an overestimation of accuracy.

We conducted this review to summarize evidence relevant to collecting and using family history in primary care. We found serious methodological limitations with the evidence on effects of collecting family history as a way to promote uptake of preventive interventions—it is insufficient to draw conclusions. The studies of the psychological effects of taking family history do not suggest particular cause for concern but also do not provide definitive evidence that taking a family history is a harmless activity. Only 1 study (13) examined effects of taking family history as part of a typical primary care activity (the periodic health examination).

Taking a family history in primary care needs to be simpler than for the standard comprehensive pedigree taken in clinical genetics (82). Four-generation pedigrees are also unlikely to be helpful in assessing the risk for complex, non-Mendelian disorders (such as those we evaluated) in most patients. Empirically based estimates of the minimum family history information that provides useful predictive power (83) would be more useful, as would confidence that the basic data (reports of relatives' disease status) are sufficiently accurate for this purpose. Finally, clinical usefulness depends on the improvement of patient outcomes as a result of this exercise. To evaluate family history–based risk assessment as a clinical intervention, controlled trials are needed to ensure that intervention effects are not confounded by psychological and behavioral patterns that participants have formed on the basis of living with “a family disease” (8485).

Few of the predictive accuracy studies we reviewed were designed to address our specific question. Almost all were classical epidemiologic investigations that assessed associations between family history and disease. The metrics used to assess strength of etiologic association between family history and disease (such as relative risk) are inappropriate for assessing how well family history classifies risk at an individual level (86). Although many of the studies we reviewed reported evidence of strong associations, as judged by relative risk and similar metrics (full data available at www.ahrq.gov), our analyses indicate that few studies achieved sensitivities much greater than 25%—regardless of the definition used.

The longitudinal analyses provided insight into different definitions of family history and their prediction of a patient's future disease risk. In contrast, the cross-sectional analyses provided information on the effectiveness of family history for identifying current disease. Given the generally low sensitivities, simple definitions based on first-degree relatives—or parental history without further elaboration—performed best. Some of the longitudinal studies were of high quality, but their heterogeneity constrained quantitative integrative analysis. The cross-sectional studies varied more in quality. Because many studies included persons who knew they had the condition of interest, we could not determine whether receiving the diagnosis had influenced the accuracy of their family history reporting or whether knowledge of their family history had led to an earlier diagnosis.

Capturing family history often involved questionnaires or interviews designed for epidemiologic research, which are not necessarily typical of current primary care practice. However, many of the definitions were simple and probably give an indication of the types of answers that would be received if elicited verbally as part of an office consultation. Although simple definitions of positive family history might not carry a high sensitivity for predicting or detecting complex disorders, they might still improve the predictive ability of other established risk factors. This might make a difference in which preventive interventions physicians recommend or how they triage patients for risky or costly screening tests (8687). Also, routine family history assessment may help to identify the small proportion of persons seen in primary care whose distinct familial disease pattern might indicate an underlying genetic predisposition that merits more extensive assessment by a geneticist.

For family history to be of value in clinical decision making, patients must report—and primary care practitioners must be able to ascertain—accurate family history information. An accurate family history is both sensitive (correctly identifying disease in relatives) and specific (correctly identifying lack of disease in relatives). When we explored questions about accuracy, we reviewed studies that were conducted in specialized clinical settings; the applicability of the findings from these studies to primary care settings may be limited. Our analyses were constrained by lack of reporting of characteristics of interest, particularly in relation to relatives. Overall, fair-quality evidence suggests that informants are better at identifying absence of disease in relatives (specificity) than at correctly reporting relatives who have been affected (sensitivity). The accuracy of family history reporting cannot be separated from the performance of the methods used to gather family history. We observed great variation in how family history was captured but could not perform a formal analysis.

Our review was largely limited to populations and settings applicable to primary care. Systematic family history collection and interpretation in specialist settings may provide evidence relevant to primary care; however, scope and pragmatic considerations limited our focus. Our emphasis on specific clinical behavioral outcomes also did not allow us to explore other effects on the part of patients, such as seeking out more extensive information from family members as a result of having been asked “the first” set of questions on family history.

Well-designed trials are required to compare the effect of clearly described, family history–based, personalized risk advice interventions with that of standard care on clinically relevant outcomes, including risk-reducing behaviors, mortality, morbidity, and evidence-based surrogate measures. Investigators also need to examine psychological effects and family and social sequelae, by using appropriate and validated instruments, and explore the effects on persons who decline to participate. Any further studies of the predictive ability of family history elements should take the way in which family history information is actually used in routine practice into account; for example, whether it is used in isolation or in combination with other risk factor data. It is debatable whether priority should be given to further studies that examine the accuracy of family history reporting in general or to those that evaluate the specific attributes of family history tools that promote accurate reporting. If further accuracy studies are conducted, attention should be given to the populations of interest and spectrum of disease risk represented.

Many health professionals regard family history enquiry as a standard element of good medical care. Occasionally, family history questions reveal unusual familial disease patterns and prompt specialist investigation. Primary care practitioners can also gain insight into patients' experiences of disease within the family, which are relevant to framing preventive advice. However, many questions remain regarding whether information gained from family history assessment improves risk prediction and chronic disease risk management, the best way to collect such information, and the positive and negative effects such collection has on patient outcomes.

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Dodani S, MacLean DD, LaPorte RE, Joffres M.  Distribution and determinants of coronary artery disease in an urban Pakistani setting. Ethn Dis. 2005; 15:429-35. PubMed
 
Scheuner MT, Whitworth WC, McGruder H, Yoon PW, Khoury MJ.  Expanding the definition of a positive family history for early-onset coronary heart disease. Genet Med. 2006; 8:491-501. PubMed
 
Magno CP, Araneta MR, Macera CA, Anderson GW.  Cardiovascular disease prevalence, associated risk factors, and plasma adiponectin levels among Filipino American women. Ethn Dis. 2008; 18:458-63. PubMed
 
Morrison AC, Fornage M, Liao D, Boerwinkle E.  Parental history of stroke predicts subclinical but not clinical stroke: the Atherosclerosis Risk in Communities Study. Stroke. 2000; 31:2098-102. PubMed
 
Jousilahti P, Rastenyte D, Tuomilehto J, Sarti C, Vartiainen E.  Parental history of cardiovascular disease and risk of stroke. A prospective follow-up of 14371 middle-aged men and women in Finland. Stroke. 1997; 28:1361-6. PubMed
 
Kadota A, Okamura T, Hozawa A, Kadowaki T, Murakami Y, Hayakawa T, et al. NIPPON DATA80 Research Group.  Relationships between family histories of stroke and of hypertension and stroke mortality: NIPPON DATA80, 1980-1999. Hypertens Res. 2008; 31:1525-31. PubMed
 
Bjørnholt JV, Erikssen G, Liestøl K, Jervell J, Thaulow E, Erikssen J.  Type 2 diabetes and maternal family history: an impact beyond slow glucose removal rate and fasting hyperglycemia in low-risk individuals? Results from 22.5 years of follow-up of healthy nondiabetic men. Diabetes Care. 2000; 23:1255-9. PubMed
 
Boer JM, Feskens EJ, Kromhout D.  Characteristics of non-insulin-dependent diabetes mellitus in elderly men: effect modification by family history. Int J Epidemiol. 1996; 25:394-402. PubMed
 
Nakanishi S, Yamane K, Kamei N, Okubo M, Kohno N.  Relationship between development of diabetes and family history by gender in Japanese-Americans. Diabetes Res Clin Pract. 2003; 61:109-15. PubMed
 
Rahman M, Simmons RK, Harding AH, Wareham NJ, Griffin SJ.  A simple risk score identifies individuals at high risk of developing Type 2 diabetes: a prospective cohort study. Fam Pract. 2008; 25:191-6. PubMed
 
Meigs JB, Cupples LA, Wilson PW.  Parental transmission of type 2 diabetes: the Framingham Offspring Study. Diabetes. 2000; 49:2201-7. PubMed
 
Mohan V, Shanthirani CS, Deepa R.  Glucose intolerance (diabetes and IGT) in a selected South Indian population with special reference to family history, obesity and lifestyle factors—the Chennai Urban Population Study (CUPS 14). J Assoc Physicians India. 2003; 51:771-7. PubMed
 
Ebbesson SO, Schraer CD, Risica PM, Adler AI, Ebbesson L, Mayer AM. et al.  Diabetes and impaired glucose tolerance in three Alaskan Eskimo populations. The Alaska-Siberia Project. Diabetes Care. 1998; 21:563-9. PubMed
 
Nyenwe EA, Odia OJ, Ihekwaba AE, Ojule A, Babatunde S.  Type 2 diabetes in adult Nigerians: a study of its prevalence and risk factors in Port Harcourt, Nigeria. Diabetes Res Clin Pract. 2003; 62:177-85. PubMed
 
Haron Y, Hussein O, Epstein L, Eilat D, Harash B, Linn S.  Type 2 diabetes among Circassians in Israel. Isr Med Assoc J. 2006; 8:622-6. PubMed
 
Gikas A, Sotiropoulos A, Panagiotakos D, Peppas T, Skliros E, Pappas S.  Prevalence, and associated risk factors, of self-reported diabetes mellitus in a sample of adult urban population in Greece: MEDICAL Exit Poll Research in Salamis (MEDICAL EXPRESS 2002). BMC Public Health. 2004; 4:2. PubMed
 
Hariri S, Yoon PW, Qureshi N, Valdez R, Scheuner MT, Khoury MJ.  Family history of type 2 diabetes: a population-based screening tool for prevention? Genet Med. 2006; 8:102-8. PubMed
 
Carlsson S, Midthjell K, Grill V.  Influence of family history of diabetes on incidence and prevalence of latent autoimmune diabetes of the adult: results from the Nord-Trøndelag Health Study. Diabetes Care. 2007; 30:3040-5. PubMed
 
Hilding A, Eriksson AK, Agardh EE, Grill V, Ahlbom A, Efendic S. et al.  The impact of family history of diabetes and lifestyle factors on abnormal glucose regulation in middle-aged Swedish men and women. Diabetologia. 2006; 49:2589-98. PubMed
 
Annis AM, Caulder MS, Cook ML, Duquette D.  Family history, diabetes, and other demographic and risk factors among participants of the National Health and Nutrition Examination Survey 1999-2002. Prev Chronic Dis. 2005; 2:A19. PubMed
 
Bindraban NR, van Valkengoed IG, Mairuhu G, Holleman F, Hoekstra JB, Michels BP. et al.  Prevalence of diabetes mellitus and the performance of a risk score among Hindustani Surinamese, African Surinamese and ethnic Dutch: a cross-sectional population-based study. BMC Public Health. 2008; 8:271. PubMed
 
Yoon PW, Scheuner MT, Peterson-Oehlke KL, Gwinn M, Faucett A, Khoury MJ.  Can family history be used as a tool for public health and preventive medicine? Genet Med. 2002; 4:304-10. PubMed
 
Ajlouni K, Khader YS, Batieha A, Ajlouni H, El-Khateeb M.  An increase in prevalence of diabetes mellitus in Jordan over 10 years. J Diabetes Complications. 2008; 22:317-24. PubMed
 
Parent ME, Ghadirian P, Lacroix A, Perret C.  Accuracy of reports of familial breast cancer in a case-control series. Epidemiology. 1995; 6:184-6. PubMed
 
Eerola H, Blomqvist C, Pukkala E, Pyrhönen S, Nevanlinna H.  Familial breast cancer in southern Finland: how prevalent are breast cancer families and can we trust the family history reported by patients? Eur J Cancer. 2000; 36:1143-8. PubMed
 
Anton-Culver H, Kurosaki T, Taylor TH, Gildea M, Brunner D, Bringman D.  Validation of family history of breast cancer and identification of the BRCA1 and other syndromes using a population-based cancer registry. Genet Epidemiol. 1996; 13:193-205. PubMed
 
Schneider KA, DiGianni LM, Patenaude AF, Klar N, Stopfer JE, Calzone KA. et al.  Accuracy of cancer family histories: comparison of two breast cancer syndromes. Genet Test. 2004; 8:222-8. PubMed
 
Kerber RA, Slattery ML.  Comparison of self-reported and database-linked family history of cancer data in a case-control study. Am J Epidemiol. 1997; 146:244-8. PubMed
 
Aitken J, Bain C, Ward M, Siskind V, MacLennan R.  How accurate is self-reported family history of colorectal cancer? Am J Epidemiol. 1995; 141:863-71. PubMed
 
Mitchell RJ, Brewster D, Campbell H, Porteous ME, Wyllie AH, Bird CC. et al.  Accuracy of reporting of family history of colorectal cancer. Gut. 2004; 53:291-5. PubMed
 
Zhu K, McKnight B, Stergachis A, Daling JR, Levine RS.  Comparison of self-report data and medical records data: results from a case-control study on prostate cancer. Int J Epidemiol. 1999; 28:409-17. PubMed
 
King TM, Tong L, Pack RJ, Spencer C, Amos CI.  Accuracy of family history of cancer as reported by men with prostate cancer. Urology. 2002; 59:546-50. PubMed
 
Soegaard M, Jensen A, Frederiksen K, Høgdall E, Høgdall C, Blaakaer J. et al.  Accuracy of self-reported family history of cancer in a large case-control study of ovarian cancer. Cancer Causes Control. 2008; 19:469-79. PubMed
 
Ziogas A, Anton-Culver H.  Validation of family history data in cancer family registries. Am J Prev Med. 2003; 24:190-8. PubMed
 
Sijmons RH, Boonstra AE, Reefhuis J, Hordijk-Hos JM, deWalle HE, Oosterwijk JC. et al.  Accuracy of family history of cancer: clinical genetic implications. Eur J Hum Genet. 2000; 8:181-6. PubMed
 
Novakovic B, Goldstein AM, Tucker MA.  Validation of family history of cancer in deceased family members. J Natl Cancer Inst. 1996; 88:1492-3. PubMed
 
Chang ET, Smedby KE, Hjalgrim H, Glimelius B, Adami HO.  Reliability of self-reported family history of cancer in a large case-control study of lymphoma. J Natl Cancer Inst. 2006; 98:61-8. PubMed
 
Aitken JF, Youl P, Green A, MacLennan R, Martin NG.  Accuracy of case-reported family history of melanoma in Queensland, Australia. Melanoma Res. 1996; 6:313-7. PubMed
 
Mussio P, Weber W, Brunetti D, Stemmermann GN, Torhorst J.  Taking a family history in cancer patients with a simple questionnaire. Anticancer Res. 1998; 18:2811-4. PubMed
 
Karter AJ, Rowell SE, Ackerson LM, Mitchell BD, Ferrara A, Selby JV. et al.  Excess maternal transmission of type 2 diabetes. The Northern California Kaiser Permanente Diabetes Registry. Diabetes Care. 1999; 22:938-43. PubMed
 
Bochud M, Burnier M, Paccaud F, Falconnet C, Mooser V, Both N. et al.  Patients' sibling history was sensitive for hypertension and specific for diabetes. J Clin Epidemiol. 2004; 57:497-501. PubMed
 
Bensen JT, Liese AD, Rushing JT, Province M, Folsom AR, Rich SS. et al.  Accuracy of proband reported family history: the NHLBI Family Heart Study (FHS). Genet Epidemiol. 1999; 17:141-50. PubMed
 
Murabito JM, Nam BH, D'Agostino RB Sr, Lloyd-Jones DM, O'Donnell CJ, Wilson PW.  Accuracy of offspring reports of parental cardiovascular disease history: the Framingham Offspring Study. Ann Intern Med. 2004; 140:434-40. PubMed
 
France CR, Page GD.  Assessing parental history of hypertension: father (and mother) knows best! Psychophysiology. 1998; 35:341-3. PubMed
 
Silberberg JS, Wlodarczyk J, Fryer J, Ray CD, Hensley MJ.  Correction for biases in a population-based study of family history and coronary heart disease. The Newcastle Family History Study I. Am J Epidemiol. 1998; 147:1123-32. PubMed
 
Klungel OH, deBoer A, Paes AH, Seidell JC, Bakker A.  Cardiovascular diseases and risk factors in a population-based study in The Netherlands: agreement between questionnaire information and medical records. Neth J Med. 1999; 55:177-83. PubMed
 
Marteau TM, Bekker H.  The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). Br J Clin Psychol. 1992; 31: (Pt 3) 301-6. PubMed
 
Lerman C, Trock B, Rimer BK, Jepson C, Brody D, Boyce A.  Psychological side effects of breast cancer screening. Health Psychol. 1991; 10:259-67. PubMed
 
Wattendorf DJ, Hadley DW.  Family history: the three-generation pedigree. Am Fam Physician. 2005; 72:441-8. PubMed
 
www.nchpeg.org/newsletter/inpracticespr04.pdfBennett R.  Is a universal family history tool feasible? Genetic Family History in Practice. 2004; 2:1-2. PubMed
 
Andersen MR, Peacock S, Nelson J, Wilson S, McIntosh M, Drescher C. et al.  Worry about ovarian cancer risk and use of ovarian cancer screening by women at risk for ovarian cancer. Gynecol Oncol. 2002; 85:3-8. PubMed
 
Werness BA, Afify AM, Bielat KL, Eltabbakh GH, Piver MS, Paterson JM.  Altered surface and cyst epithelium of ovaries removed prophylactically from women with a family history of ovarian cancer. Hum Pathol. 1999; 30:151-7. PubMed
 
Pepe MS, Janes H, Longton G, Leisenring W, Newcomb P.  Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. Am J Epidemiol. 2004; 159:882-90. PubMed
 
Boyko EJ, Alderman BW.  The use of risk factors in medical diagnosis: opportunities and cautions. J Clin Epidemiol. 1990; 43:851-8. PubMed
 
de Luis DA, Sagrado MG, Aller R, Izaola O, Conde R.  Influence of ALA54THR polymorphism of fatty acid-binding protein 2 on obesity and cardiovascular risk factors. Horm Metab Res. 2007; 39:830-4. PubMed
 
Fletcher RH, Lobb R, Bauer MR, Kemp JA, Palmer RC, Kleinman KP. et al.  Screening patients with a family history of colorectal cancer. J Gen Intern Med. 2007; 22:508-13. PubMed
 
Cappelli M, Surh L, Walker M, Korneluk Y, Humphreys L, Verma S. et al.  Psychological and social predictors of decisions about genetic testing for breast cancer in high-risk women. Psychol Health Med. 2001; 6:321-33. PubMed
 
Williams KP, Sheppard VB, Todem D, Mabiso A, Wulu JT Jr, Hines RD.  Family matters in mammography screening among African-American women age > 40. J Natl Med Assoc. 2008; 100:508-15. PubMed
 
Gil F, Méndez I, Sirgo A, Llort G, Blanco I, Cortés-Funes H.  Perception of breast cancer risk and surveillance behaviours of women with family history of breast cancer: a brief report on a Spanish cohort. Psychooncology. 2003; 12:821-7. PubMed
 
Helfand BT, Loeb S, Cashy J, Meeks JJ, Thaxton CS, Han M, et al.  Tumor characteristics of carriers and noncarriers of the deCODE 8q24 prostate cancer susceptibility alleles. J Urol. 2008;179:2197-201; discussion 2202. [PMID: 18423739]
 
Longacre AV, Cramer LD, Gross CP.  Screening colonoscopy use among individuals at higher colorectal cancer risk. J Clin Gastroenterol. 2006; 40:490-6. PubMed
 
Traurig M, Hanson RL, Kobes S, Bogardus C, Baier LJ.  Protein tyrosine phosphatase 1B is not a major susceptibility gene for type 2 diabetes mellitus or obesity among Pima Indians. Diabetologia. 2007; 50:985-9. PubMed
 
Petrisek A, Campbell S, Laliberte L.  Family history of breast cancer. Impact on the disease experience. Cancer Pract. 2000; 8:135-42. PubMed
 
Madlensky L, Flatt SW, Bardwell WA, Rock CL, Pierce JP, WHEL Study group.  Is family history related to preventive health behaviors and medical management in breast cancer patients? Breast Cancer Res Treat. 2005; 90:47-54. PubMed
 
Silberberg JS, Wlodarczyk J, Fryer J, Robertson R, Hensley MJ.  Risk associated with various definitions of family history of coronary heart disease. The Newcastle Family History Study II. Am J Epidemiol. 1998; 147:1133-9. PubMed
 
Bloom JR, Stewart SL, Oakley-Girvans I, Banks PJ, Chang S.  Family history, perceived risk, and prostate cancer screening among African American men. Cancer Epidemiol Biomarkers Prev. 2006; 15:2167-73. PubMed
 
Jacobsen PB, Lamonde LA, Honour M, Kash K, Hudson PB, Pow-Sang J.  Relation of family history of prostate cancer to perceived vulnerability and screening behavior. Psychooncology. 2004; 13:80-5. PubMed
 

Figures

Tables

Table Jump PlaceholderTable.  Summary of Reviewed Studies

References

Williams RR, Hunt SC, Heiss G, Province MA, Bensen JT, Higgins M. et al.  Usefulness of cardiovascular family history data for population-based preventive medicine and medical research (the Health Family Tree Study and the NHLBI Family Heart Study). Am J Cardiol. 2001; 87:129-35. PubMed
CrossRef
 
Hawe E, Talmud PJ, Miller GJ, Humphries SE, Second Northwick Park Heart Study.  Family history is a coronary heart disease risk factor in the Second Northwick Park Heart Study. Ann Hum Genet. 2003; 67:97-106. PubMed
 
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Meigs JB, Cupples LA, Wilson PW.  Parental transmission of type 2 diabetes: the Framingham Offspring Study. Diabetes. 2000; 49:2201-7. PubMed
 
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Molyneaux L, Constantino M, Yue D.  Strong family history predicts a younger age of onset for subjects diagnosed with type 2 diabetes. Diabetes Obes Metab. 2004; 6:187-94. PubMed
 
Nakanishi S, Yamane K, Kamei N, Okubo M, Kohno N.  Relationship between development of diabetes and family history by gender in Japanese-Americans. Diabetes Res Clin Pract. 2003; 61:109-15. PubMed
 
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Qureshi N, Standen PJ, Hapgood R, Hayes J.  A randomized controlled trial to assess the psychological impact of a family history screening questionnaire in general practice. Fam Pract. 2001; 18:78-83. PubMed
 
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Cauley JA, Song J, Dowsett SA, Mershon JL, Cummings SR.  Risk factors for breast cancer in older women: the relative contribution of bone mineral density and other established risk factors. Breast Cancer Res Treat. 2007; 102:181-8. PubMed
 
Halapy E, Chiarelli AM, Klar N, Knight JA.  Accuracy of breast screening among women with and without a family history of breast and/or ovarian cancer. Breast Cancer Res Treat. 2005; 90:299-305. PubMed
 
Denic S, Bener A.  Consanguinity decreases risk of breast cancer—cervical cancer unaffected. Br J Cancer. 2001; 85:1675-9. PubMed
 
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Wei EK, Giovannucci E, Wu K, Rosner B, Fuchs CS, Willett WC. et al.  Comparison of risk factors for colon and rectal cancer. Int J Cancer. 2004; 108:433-42. PubMed
 
Sandhu MS, Luben R, Khaw KT.  Prevalence and family history of colorectal cancer: implications for screening. J Med Screen. 2001; 8:69-72. PubMed
 
Byeon JS, Yang SK, Kim TI, Kim WH, Lau JY, Leung WK, et al. for the Asia Pacific Working Group for Colorectal Cancer.  Colorectal neoplasm in asymptomatic Asians: a prospective multinational multicenter colonoscopy survey. Gastrointest Endosc. 2007; 65:1015-22. PubMed
 
Rodríguez C, Calle EE, Miracle-McMahill HL, Tatham LM, Wingo PA, Thun MJ. et al.  Family history and risk of fatal prostate cancer. Epidemiology. 1997; 8:653-7. PubMed
 
Ahn J, Moslehi R, Weinstein SJ, Snyder K, Virtamo J, Albanes D.  Family history of prostate cancer and prostate cancer risk in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Int J Cancer. 2008; 123:1154-9. PubMed
 
Cerhan JR, Parker AS, Putnam SD, Chiu BC, Lynch CF, Cohen MB. et al.  Family history and prostate cancer risk in a population-based cohort of Iowa men. Cancer Epidemiol Biomarkers Prev. 1999; 8:53-60. PubMed
 
Chen YC, Page JH, Chen R, Giovannucci E.  Family history of prostate and breast cancer and the risk of prostate cancer in the PSA era. Prostate. 2008; 68:1582-91. PubMed
 
Mäkinen T, Tammela TL, Stenman UH, Määttänen L, Rannikko S, Aro J. et al.  Family history and prostate cancer screening with prostate-specific antigen. J Clin Oncol. 2002; 20:2658-63. PubMed
 
Kalish LA, McDougal WS, McKinlay JB.  Family history and the risk of prostate cancer. Urology. 2000; 56:803-6. PubMed
 
Sesso HD, Lee IM, Gaziano JM, Rexrode KM, Glynn RJ, Buring JE.  Maternal and paternal history of myocardial infarction and risk of cardiovascular disease in men and women. Circulation. 2001; 104:393-8. PubMed
 
Piros S, Karlehagen S, Lappas G, Wilhelmsen L.  Risk factors for myocardial infarction among Swedish railway engine drivers during 10 years follow-up. J Cardiovasc Risk. 2000; 7:395-400. PubMed
 
Jousilahti P, Puska P, Vartiainen E, Pekkanen J, Tuomilehto J.  Parental history of premature coronary heart disease: an independent risk factor of myocardial infarction. J Clin Epidemiol. 1996; 49:497-503. PubMed
 
Hippe M, Vestbo J, Hein HO, Borch-Johnsen K, Jensen G, Sørensen TI.  Familial predisposition and susceptibility to the effect of other risk factors for myocardial infarction. J Epidemiol Community Health. 1999; 53:269-76. PubMed
 
Djoussé L, Gaziano JM.  Parental history of myocardial infarction and risk of heart failure in male physicians. Eur J Clin Invest. 2008; 38:896-901. PubMed
 
Dodani S, MacLean DD, LaPorte RE, Joffres M.  Distribution and determinants of coronary artery disease in an urban Pakistani setting. Ethn Dis. 2005; 15:429-35. PubMed
 
Scheuner MT, Whitworth WC, McGruder H, Yoon PW, Khoury MJ.  Expanding the definition of a positive family history for early-onset coronary heart disease. Genet Med. 2006; 8:491-501. PubMed
 
Magno CP, Araneta MR, Macera CA, Anderson GW.  Cardiovascular disease prevalence, associated risk factors, and plasma adiponectin levels among Filipino American women. Ethn Dis. 2008; 18:458-63. PubMed
 
Morrison AC, Fornage M, Liao D, Boerwinkle E.  Parental history of stroke predicts subclinical but not clinical stroke: the Atherosclerosis Risk in Communities Study. Stroke. 2000; 31:2098-102. PubMed
 
Jousilahti P, Rastenyte D, Tuomilehto J, Sarti C, Vartiainen E.  Parental history of cardiovascular disease and risk of stroke. A prospective follow-up of 14371 middle-aged men and women in Finland. Stroke. 1997; 28:1361-6. PubMed
 
Kadota A, Okamura T, Hozawa A, Kadowaki T, Murakami Y, Hayakawa T, et al. NIPPON DATA80 Research Group.  Relationships between family histories of stroke and of hypertension and stroke mortality: NIPPON DATA80, 1980-1999. Hypertens Res. 2008; 31:1525-31. PubMed
 
Bjørnholt JV, Erikssen G, Liestøl K, Jervell J, Thaulow E, Erikssen J.  Type 2 diabetes and maternal family history: an impact beyond slow glucose removal rate and fasting hyperglycemia in low-risk individuals? Results from 22.5 years of follow-up of healthy nondiabetic men. Diabetes Care. 2000; 23:1255-9. PubMed
 
Boer JM, Feskens EJ, Kromhout D.  Characteristics of non-insulin-dependent diabetes mellitus in elderly men: effect modification by family history. Int J Epidemiol. 1996; 25:394-402. PubMed
 
Nakanishi S, Yamane K, Kamei N, Okubo M, Kohno N.  Relationship between development of diabetes and family history by gender in Japanese-Americans. Diabetes Res Clin Pract. 2003; 61:109-15. PubMed
 
Rahman M, Simmons RK, Harding AH, Wareham NJ, Griffin SJ.  A simple risk score identifies individuals at high risk of developing Type 2 diabetes: a prospective cohort study. Fam Pract. 2008; 25:191-6. PubMed
 
Meigs JB, Cupples LA, Wilson PW.  Parental transmission of type 2 diabetes: the Framingham Offspring Study. Diabetes. 2000; 49:2201-7. PubMed
 
Mohan V, Shanthirani CS, Deepa R.  Glucose intolerance (diabetes and IGT) in a selected South Indian population with special reference to family history, obesity and lifestyle factors—the Chennai Urban Population Study (CUPS 14). J Assoc Physicians India. 2003; 51:771-7. PubMed
 
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Suppression of renin-angiotensin system (RAS) and cardiovascular protection
Posted on January 2, 2010
Jose R Banegas
Department of Preventive Medicine, School of Medicine, Autonomous University of Madrid, Spain
Conflict of Interest: None Declared

TO THE EDITOR: We read with great interest the paper published by Baker et al in Ann Intern Med comparing effectiveness of angiotensin- converting enzyme inhibitors (ACEi) or angiotensin II-receptor blockers (ARB) for ischemic heart disease (1). The topic of suppression of renin- angiotensin system (RAS) and cardiovascular and renal protection has been objective of different reviews and meta-analyses in the last years. In fact, one of the topics of discussion when ACEi and ARB were compared was a potential difference in the protection of myocardial infarction in favour of ACEi (2), but this possibility has been denied by others (3).

The reality is that when studies using ACEi or ARB have been compared, little or no attention was paid to the fact that the circumstances under which those studies were performed differed. Most if not all patients entering ACEi studies were performed naive of having received a drug suppressing the RAS, which is not the case for those patients entering ARB studies. A clear example is the ONTARGET-TRANSCEND project (4). In TRANSCEND, every body had received and ACEi for periods of time not defined, but it could have been years. In ONTARGET, almost two thirds had received an ACEi before admission in the study. Hence, the development of cardiorenal disease in many of those patients entering ARB studies took place while on suppression of the RAS. Should this be the case, the capacity of a new RAS suppressor to modify the evolution of cardiorenal disease should be diminished in a very important amount. This is the most important argument to perform studies in patients having developed cardiorenal disease under suppression of the RAS and to reconsider the different possible ways to increase the degree of suppression of the RAS (ACEi plus ARB, ACEi or ARB plus aliskiren, ACEi or ARB uptitration, ACEi or ARB plus aldosterone blockers).

On the other hand, many more patients were taking lipid-lowering drugs in trials testing the capacity of ARB to protect cardiovascular and kidney systems (4), which could have interfered in the interpretation of the outcome data, in particular in patients non naive of RAS suppression before entering the study.

In summary, conclusions of the comparison of studies with ACEi and ARB have to be considered with caution. Design of new studies must contemplate all possible confounders.

References 1. Baker WL, Coleman CI, Kluger J, Reinhart KM, Talati R, Quercia R, et al. Systematic review: comparative effectiveness of angiotensin-converting enzyme inhibitors or angiotensin II-receptor blockers for ischemic heart disease. Ann Intern Med. 2009;151:861-71.

2. Strauss MH, Hall AS. Angiotensin receptor blockers may increase risk of myocardial infarction: unraveling the ARB-MI paradox. Circulation. 2006;114: 838-54.

3. Volpe M, Tocci G, Sciarretta S, Verdecchia P, Trimarco B, Mancia G. Angiotensin II receptor blockers and myocardial infarction: an updated analysis of randomized clinical trials. J Hypertens. 2009;27:941-46.

4. Yusuf S, Teo KK, Pogue J, Dyal L, Copland I, Schumacher H, et al. ONTARGET Investigators. Telmisartan, ramipril or both in patients at high risk for vascular events. N Engl J Med. 2008;358:1547-59.

Authors Julian Segura, MDa; Jose R. Banegas, MD, MPHb; Luis M. Ruilope, MD, PhDa a.Hypertension Unit. Hospital 12 de Octubre. Madrid. Spain. b.Department of Preventive Medicine and Public Health, Universidad Autonoma de Madrid. CIBERESP. Madrid, Spain.

Conflict of Interest:

None declared

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