Case-Control Study Quality Appraisal

The assignment focuses on critically evaluating the quality of a published case-control study investigating risk factors for pancreatic cancer. Students are tasked with analyzing various aspects of the study design, including confounding factors, selection of controls, sample size, and data collection methods. The appraisal considers internal validity (accuracy of results), external validity (generalizability to other populations), precision (measurement accuracy), and potential biases. The goal is to determine the overall strength and reliability of the study's findings.

Running head: ANALYTIC APPROACHES IN EPIDEMIOLOGY 1
Analytic Approaches in Epidemiology
Student’s Name
Institutional Affiliation

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Introduction
The current paper seeks to critically analyze the study by Hassan, Bondy, Wolff,
Abbruzzese, Vauthey, Pisters, Evans, Khan, Chou, Lenzi, and Li (2007). By doing so, the
validity and usefulness of the findings will be assessed. Since Hassan, et al (2007)’s research was
a case-control study, the tool provided by the CASP (Critical Appraisal Skills Programme) will
be used (case control study) to guide the appraisal. The paper will also determine the extent to
which there is a causal association between pancreatic cancer-which is the main outcome- and
consumption of alcohol, smoking of cigarette, pancreatic cancer family history, diabetes
mellitus, and history of pancreatitis. Overall, Hassan, et al (2007)’s study is found to be of good
quality since its methodological strengths surpass its weaknesses, and it has internal and external
validity.
CASP Tool for Case Control Study
The critical appraisal tool for evaluating case control studies is composed of three wide
matters that should be put into consideration, validity of the findings, what the findings are, and
whether the findings will help locally (CASP, 2017). The three issues are then broken down into
a total of 11 questions, which will be used to guide evaluation of the chosen article.
Validity of the Results
The authors addressed a clearly focused issue since the objective of carrying out the
research was evident with a clear outline of the population and risk factors being investigated. A
case control was appropriate to answer the question since pancreatic cancer is a rare condition.
As Song and Chung (2010) outlines, case controls are suited well when investigating rare

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outcomes. Also, case control studies allow for more than one risk factor to be evaluated for a just
one outcome (Song and Chung, 2010). In Hassan, et al (2007)’s study, multiple risk factors
including, heavy intake alcohol intake, pancreatic cancer cigarette smoking, and pancreatitis
family history, and diabetes mellitus were all examined for pancreatic cancer.
The authors used hospital-based case-control. The cases were incident as they were
selected from patients that had recently been diagnosed with pancreatic cancer. As CLIO (2004)
outlines, using incident cases as opposed to prevalent increases confidence that exposures
occurrence were before the outcome disease’s onset. Additionally, using incident cases ensured
no cases of over-representation of long duration. The number of cases selected was significantly
large (808 participants) and were varying with age, ethnicity, sex, and social classes, ensuring
that they were a representative of a defined population. The exclusion and inclusion criterion was
clear ensuring consistency in the characteristics of cases. All the cases had been diagnosed with
pancreatic ductal adenocarcinoma, resided in the U.S. and would communicate in English.
Patients with other types of cancers were excluded together with those with past history of
cancer. As such, the cases were selected in an acceptable way.
When recruiting controls, the authors were keen to avoid bias. Controls were chosen from
healthy friends as well as genetically unrelated members of the patients’ family with other cancer
types other than pancreatic cancer. This would help minimize selection bias by excluding first
degree and relatives that are not related by genetics but with pancreatic cancer as controls since
the former may have genetic factors related to the outcome while thelatter may share the same
lifestyle factors that may predispose them to the disease such as dietary habits. Therefore, by
doing so the study would determine the true relationship between pancreatic cancer and some

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risk factors such as family history of the disease, cigarette smoking, and environmental factors
without the link being altered.
The controls were in many ways similar to the cases. The authors used matching where
the cases and controls were frequently matched by factors such as age, ethnicity, and sex. As
Rose and Laan (2009) suggests, matching helps to increase the efficiency of the study by
allowing similar distributions across confounding variables between case and controls. Although
some scholars such as Pearce (2016) argue that matching does not eliminate confounding but
instead may introduce it by the matching factors, it is more feasible that matched sampling
results to balancing controls and cases across the chosen matching variable levels, thus reducing
variance and improving statistical efficiency (Rose and Laan, 2009). As such, Hassan, et al
(2007) improved the efficiency of their study through matching.
A study’s validity is also determined by the rate of non-response. According to Groves
(2006) high non-response can lead to non-response bias. In Hassan, et al (2007)’s study, the non-
response rate was 19.4% with the reasons for failure to participate varying. However, the authors
justified that statistical analysis showed that there was no significant differences between missed
and selected patients based on sex, race/ethnicity, age, residency state, and educational level. As
such, the study was free from non-response bias. The quality of case control studies is
contributed by the number of cases and controls selected. In the current study under appraisal,
the authors recruited the same number of cases and controls. Selecting equal number increases
the efficiency of a study as BMJ (n.d.) states. However, the cases comprised older individuals
and had lower level of education compared to controls, an aspect that may have interfered with
the study results.

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Ascertainment of exposure may also impact on the validity and reliability of a study. Just
like most case-control studies, Hassan, et al (2017)’s study established exposure from personal
recall by means of self administered questionnaire and structured interviews. As BMJ (n.d.)
states, the validity of information from personal recall depend significantly on the subject matter.
Therefore, it may have been difficult for some participants to remember their past habits,
reducing the reliability of the findings. For instance, one of the risk factors sought to be
investigated by Hassan, et al (2007) was dietary habits. Recall bias may have resulted since it
may be problematic for individuals to remember their past nutritional habits. Additionally, it is
more likely that cases may remember past exposures than controls since they may have figured
the potential causes of their conditions. As Carlson and Morrison (2009) states, bias may result if
controls and cases recall differently past experiences.
Confounding factors may affect the findings of a study as they may distort the true
association between variables. They may falsely demonstrate an evident or mask an association
between a risk factor and an outcome when there is no existence of any relationship (Skelly,
Dettroli, Brodt, 2012). Hassan, et al (2007) addressed various confounding such as exposure to
tobacco, use of alcohol, and chronic illnesses. Other important confounding factors accounted for
by the authors are genetic and lifestyle considerations where they excluded first degree relatives
and spouses respectively. These factors may increase the risk of developing pancreatic cancer.
Therefore, by the authors recruiting controls that were considered free from exposure to them
they decreased the effect of confounding on the study.
What the Results Are

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Hassan, et al (2007)’s findings revealed that diabetes mellitus, heavy consumption of
alcohol, history of pancreatitis, pancreatic cancer family history, and cigarette smoking were
significant pancreatic cancer risk factors. The study also revealed synergistic interactions
between family pancreatic cancer family history, cigarette smoking, and type 2 diabetes in
women. The results were adjusted for confounding and the associations were most likely
insignificantly affected by these factors.
The precision of a research finding is an important determinant of the quality of the
study. Precision can be indicated by sample size and study’s efficiency (Carlson and Morrison,
2009). Overall, Hassan, et al (2007)’s study provided precise results since they included balanced
groups of non-exposed, exposed, without outcome, and with outcome. Additionally, the adjusted
odds ratio had narrow confidence intervals, indicating high precision in estimating the
associations.
Whether the Results Will Help Locally
Hassan, et al (2007) incorporated a significant number of participants in their study.
Additionally, participants were composed of people from different geographic areas, ages, and
ethnic groups, making it representative. Therefore, the results can be generalized to a more
universal population. Therefore, the study has external validity
Conclusion
The study by Hassan, et al (2017) can be deemed of good quality based on the current
appraisal. Although it was found to have some weaknesses such as recall bias, its precision and
internal and external validity were not compromised. The authors addressed most of the issues

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that may lower the quality of the study such as confounding factors, selection of cases and
controls, addressed a clearly focused question, and chose controls effectively. As such, the study
can be applied to the general population and can be used to support evidence-based healthcare
coupled with other evidences from other research studies.
References
BMJ. (n.d.). chapter 8: case-control and cross sectional studies. The BMJ. Retrieved from
http://www.bmj.com/about-bmj/resources-readers/publications/epidemiology-
uninitiated/8-case-control-and-cross-sectional
Carlson, M.D.A., & Morrison, R.S. (2009). Study design, precision, and validity in observational
studies. Journal of Palliative Medicine. 12(1), 77-82.
CLIO. (2004). Incident vs. Prevalent cases. CLIO Learning Modules. Retrieved from
http://cliomods.stanford.edu/trailmaps/selection/case-control/incident-vs-prevalent-
cases/index.html
Critical Appraisal Skills Program, (CASP). (2017). Critical appraisal checklist, case control
studies. Retrieved from http://www.casp-uk.net/#!casp-international/c1zsi
Groves, R.M. (2006). Nonresponse rates and nonresponse bias in houseghold surveys. Public
Opinion Quarterrly. 70(5), 646-675.
Hassan, M.M., Bondy, M.L., Wolff, R.A., Abbruzzese, J.L., Vauthey, J., Pisters, P.W., Evans,
B., Khan, R., Chou, T., Lenzi, R., &Li, D. (2007). Risk factors for pancreatic cancer:
case-control study. Am J Gastroenterol, 102(12), 2696-2707.

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Pearce, N. (2016). Analysis of matched case-control studies. BMJ. 352
Rose, S. & Laan, M.J. (2009). Why match? Investigating matched case-control study designs
with causal effect estimation. The International Journal of Biostatistics. 5(1)
Skelly, C.A., Dettroli, J.R., & Brodt, D.E. (2012). Assessing bias: the importance of considering
confounding. Evidence-Based Spine-Care Journal. 3(1), 9-12.
Song, J.W. & Chung, K.C. (2010). Observational studies: cohort and case-control studies. Plast
Reconstr Surg. 126(6), 2234-2242.
Young, J.M. & Solomon, J.M. (2009). How to criticaaly appraise an article. Nature Reviews
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