The aim of the authors was to assess the validity and agreement of
self-reported prevalent cases of stroke and AMI in the Spanish cohort of
the European Prospective Investigation into Cancer and Nutrition (EPIC).
They calculated sensitivity, specificity, positive predictive values and ?
statistics. The sensitivity of self-reported prevalent cases of stroke was
81.3% and that for AMI was 97.7%. The positive predictive value was 22.2%
and 60.7% for stroke and AMI, respectively. The agreement between self-
report questionnaire results and medical records was substantial (?=0.75)
for AMI but not for stroke (?=0.35).1
To scientifically assess the accuracy (validity) of a test, there are 7
estimations named Sensitivity, Specificity, Positive Predictive Value
(PPV), Negative Predictive Value (NPV), Likelihood ratio positive, LR+
(true positive/false positive), Likelihood ratio negative, LR- (false
negative/true negative) and finally Odds ratio, OR (true results /false
results).2 Considering limitations of the first 4 estimations, preferably
the last 3 estimations are being reported. However, due to the different
range of these estimations [(LR+ from 1 to infinity; the higher, the
better) (LR- from 0 to 1; the closer to the zero, the better) and OR
greater than 50 indicates a valid test), usually two different tests are
being evaluated compared to a gold standard. 2
Regarding agreement, to compute kappa value, just concordant cells are
being considered, whereas discordant cells should also be taking into
account in order to reach a correct estimation of agreement (Weighted
kappa).2-4
It is crucial to know that there is no value of kappa that can be regarded
universally as indication good agreement. Statistics cannot provide a
simple substitute for clinical judgment. Two important weaknesses of k
value to assess agreement of a qualitative variable are as follow: It
depends upon the prevalence in each category and also depends upon the
number of categories. So it is obvious that the less our categories, the
higher will be our kappa value which can easily lead to
misinterpretation.2-4
S.Sabour, MD, PhD
References:
1- Mach?n M, Arriola L, Larra?aga N, Amiano P, Moreno-Iribas C, Agudo A,
Ardanaz E, Barricarte A, Buckland G, Chirlaque MD, Gavrila D, Huerta JM,
Mart?nez C, Molina E, Navarro C, Quiros JR, Rodr?guez L, Sanchez MJ,
Gonz?lez CA, Dorronsoro M. Validity of self-reported prevalent cases of
stroke and acute myocardial infarction in the Spanish cohort of the EPIC
study. J Epidemiol Community Health. 2012 May 10
2- Epidemiology, biostatistics and preventive medicine, Jeckel, 1st
edition, 2008
3- Modern Epidemiology, K. Rothman, 3 rd edition, 2010
4- Clinical Epidemiology, D.E Grobbee, 1st edition, 2010
Conflict of Interest:
None declared
The aim of the authors was to assess the validity and agreement of self-reported prevalent cases of stroke and AMI in the Spanish cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC). They calculated sensitivity, specificity, positive predictive values and ? statistics. The sensitivity of self-reported prevalent cases of stroke was 81.3% and that for AMI was 97.7%. The positive predictive value was 22.2% and 60.7% for stroke and AMI, respectively. The agreement between self- report questionnaire results and medical records was substantial (?=0.75) for AMI but not for stroke (?=0.35).1 To scientifically assess the accuracy (validity) of a test, there are 7 estimations named Sensitivity, Specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), Likelihood ratio positive, LR+ (true positive/false positive), Likelihood ratio negative, LR- (false negative/true negative) and finally Odds ratio, OR (true results /false results).2 Considering limitations of the first 4 estimations, preferably the last 3 estimations are being reported. However, due to the different range of these estimations [(LR+ from 1 to infinity; the higher, the better) (LR- from 0 to 1; the closer to the zero, the better) and OR greater than 50 indicates a valid test), usually two different tests are being evaluated compared to a gold standard. 2 Regarding agreement, to compute kappa value, just concordant cells are being considered, whereas discordant cells should also be taking into account in order to reach a correct estimation of agreement (Weighted kappa).2-4 It is crucial to know that there is no value of kappa that can be regarded universally as indication good agreement. Statistics cannot provide a simple substitute for clinical judgment. Two important weaknesses of k value to assess agreement of a qualitative variable are as follow: It depends upon the prevalence in each category and also depends upon the number of categories. So it is obvious that the less our categories, the higher will be our kappa value which can easily lead to misinterpretation.2-4
S.Sabour, MD, PhD
References: 1- Mach?n M, Arriola L, Larra?aga N, Amiano P, Moreno-Iribas C, Agudo A, Ardanaz E, Barricarte A, Buckland G, Chirlaque MD, Gavrila D, Huerta JM, Mart?nez C, Molina E, Navarro C, Quiros JR, Rodr?guez L, Sanchez MJ, Gonz?lez CA, Dorronsoro M. Validity of self-reported prevalent cases of stroke and acute myocardial infarction in the Spanish cohort of the EPIC study. J Epidemiol Community Health. 2012 May 10
2- Epidemiology, biostatistics and preventive medicine, Jeckel, 1st edition, 2008 3- Modern Epidemiology, K. Rothman, 3 rd edition, 2010 4- Clinical Epidemiology, D.E Grobbee, 1st edition, 2010
Conflict of Interest:
None declared