Using a structured questionnaire (the IQCODE) to detect individuals who may go on to develop dementia


Accurately identifying people with dementia is an area of public and professional concern. Dementia is often not diagnosed until late in the disease, and this may limit timely access to appropriate health and social support. There is a growing interest in tests that detect dementia at an early stage, before symptoms have become problematic or noticeable. One way to do this is to test a person and then re-assess them over time to see if they have developed dementia.

Our review focused on the accuracy of a questionnaire-based assessment for dementia, called the IQCODE (Informant Questionnaire for Cognitive Decline in the Elderly). We described whether the initial IQCODE score can identify people who will develop dementia months or years after their first IQCODE assessment.

We searched electronic databases of published research studies, looking for all studies that looked at IQCODE and a later diagnosis of dementia. We searched from the first available papers in scientific databases up to and including January 2016.

Study characteristics

We found three relevant studies, all of which were carried out in specific hospital settings. Two papers only included patients with acute stroke, and the other included those who had sustained a hip fracture. The papers differed in many other ways, so we we were unable to estimate a summary of their combined results. In general, a 'positive' IQCODE picked up patients who would go on to develop dementia (good sensitivity), but mislabelled a number who did not develop dementia (poor specificity). We cannot make recommendations for current practice, based on the studies we reviewed.

Quality of the evidence

The included studies demonstrated some of the challenges of research that follows people at risk of dementia over time. Not all the studies had a robust method of ensuring that none of the included participants had dementia at the start of the study, and that only new cases were identified. Similarly, many of the participants included at the start of the study were not available for re-assessment, due to death or other illness.

The review was performed by a team based in research centres in the UK (Glasgow, Edinburgh, Oxford). We had no external funding specific to this study, and we have no conflicts of interest that may have influenced our assessment of the research data.

Authors' conclusions: 

Included studies were heterogenous, recruited from specialist settings, and had potential biases. The studies identified did not allow us to make specific recommendations on the use of the IQCODE for the future detection of dementia in clinical practice. The included studies highlighted the challenges of delayed verification dementia research, with issues around prevalent dementia assessment, loss to follow-up over time, and test non-completion potentially limiting the studies. Future research should recognise these issues and have explicit protocols for dealing with them.

Read the full abstract...

The Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) is a structured interview based on informant responses that is used to assess for possible dementia. IQCODE has been used for retrospective or contemporaneous assessment of cognitive decline. There is considerable interest in tests that may identify those at future risk of developing dementia. Assessing a population free of dementia for the prospective development of dementia is an approach often used in studies of dementia biomarkers. In theory, questionnaire-based assessments, such as IQCODE, could be used in a similar way, assessing for dementia that is diagnosed on a later (delayed) assessment.


To determine the accuracy of the informant-based questionnaire IQCODE for the early detection of dementia across a variety of health care settings.

Search strategy: 

We searched these sources on 16 January 2016: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE Ovid SP, Embase Ovid SP, PsycINFO Ovid SP, BIOSIS Previews on Thomson Reuters Web of Science, Web of Science Core Collection (includes Conference Proceedings Citation Index) on Thomson Reuters Web of Science, CINAHL EBSCOhost, and LILACS BIREME. We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects, in the Cochrane Library); HTA Database (Health Technology Assessment Database, in the Cochrane Library), and ARIF (Birmingham University). We checked reference lists of included studies and reviews, used searches of included studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel, and included terms relating to cognitive tests, cognitive screening, and dementia. We used standardised database subject headings, such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate.

Selection criteria: 

We selected studies that included a population free from dementia at baseline, who were assessed with the IQCODE and subsequently assessed for the development of dementia over time. The implication was that at the time of testing, the individual had a cognitive problem sufficient to result in an abnormal IQCODE score (defined by the study authors), but not yet meeting dementia diagnostic criteria.

Data collection and analysis: 

We screened all titles generated by the electronic database searches, and reviewed abstracts of all potentially relevant studies. Two assessors independently checked the full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reported quality using the STARDdem tool.

Main results: 

From 85 papers describing IQCODE, we included three papers, representing data from 626 individuals. Of this total, 22% (N = 135/626) were excluded because of prevalent dementia. There was substantial attrition; 47% (N = 295) of the study population received reference standard assessment at first follow-up (three to six months) and 28% (N = 174) received reference standard assessment at final follow-up (one to three years). Prevalence of dementia ranged from 12% to 26% at first follow-up and 16% to 35% at final follow-up.

The three studies were considered to be too heterogenous to combine, so we did not perform meta-analyses to describe summary estimates of interest. Included patients were poststroke (two papers) and hip fracture (one paper). The IQCODE was used at three thresholds of positivity (higher than 3.0, higher than 3.12 and higher than 3.3) to predict those at risk of a future diagnosis of dementia. Using a cut-off of 3.0, IQCODE had a sensitivity of 0.75 (95%CI 0.51 to 0.91) and a specificity of 0.46 (95%CI 0.34 to 0.59) at one year following stroke. Using a cut-off of 3.12, the IQCODE had a sensitivity of 0.80 (95%CI 0.44 to 0.97) and specificity of 0.53 (95C%CI 0.41 to 0.65) for the clinical diagnosis of dementia at six months after hip fracture. Using a cut-off of 3.3, the IQCODE had a sensitivity of 0.84 (95%CI 0.68 to 0.94) and a specificity of 0.87 (95%CI 0.76 to 0.94) for the clinical diagnosis of dementia at one year after stroke.

In generaI, the IQCODE was sensitive for identification of those who would develop dementia, but lacked specificity. Methods for both excluding prevalent dementia at baseline and assessing for the development of dementia were varied, and had the potential to introduce bias.