Use of External Rates in Nested Case-Control Studies with Application to the International Radiation Study of Cervical Cancer Patients

Biometrics ◽  
1992 ◽  
Vol 48 (3) ◽  
pp. 781 ◽  
Author(s):  
Duncan C. Thomas ◽  
Maria Blettner ◽  
Nicholas E. Day
Keyword(s):  
Cervical Cancer ◽  
Cancer Patients ◽  
Case Control ◽  
Case Control Studies ◽  
Radiation Study ◽  
Nested Case Control

scholarly journals Serological response to HPV16 in CIN-III and cervical-cancer patients. Case-control studies in Spain and Colombia

1996 ◽  
Vol 66 (1) ◽  
pp. 70-74 ◽  
Author(s):  
Silvia De Sanjosé ◽  
Eva Hamsikova ◽  
Nubia Muñoz ◽  
F. Xavier Bosch ◽  
Vanda Hofmannová ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cancer Patients ◽  
Case Control ◽  
Serological Response ◽  
Case Control Studies ◽  
Cin Iii

scholarly journals A systematic assessment of the association between frequently prescribed medicines and the risk of common cancers: a series of nested case-control studies

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
R. D. McDowell ◽  
C. Hughes ◽  
P. Murchie ◽  
C. Cardwell
Keyword(s):  
Cancer Risk ◽  
Conditional Logistic Regression ◽  
Exposure Dose ◽  
Case Control ◽  
Case Control Studies ◽  
Systematic Assessment ◽  
Exposure Response ◽  
Prescribed Medicines ◽  
Nested Case Control ◽  
Novel Associations

Abstract Background Studies systematically screening medications have successfully identified prescription medicines associated with cancer risk. However, adjustment for confounding factors in these studies has been limited. We therefore investigated the association between frequently prescribed medicines and the risk of common cancers adjusting for a range of confounders. Methods A series of nested case-control studies were undertaken using the Primary Care Clinical Informatics Unit Research (PCCIUR) database containing general practice (GP) records from Scotland. Cancer cases at 22 cancer sites, diagnosed between 1999 and 2011, were identified from GP records and matched with up to five controls (based on age, gender, GP practice and date of registration). Odds ratios (OR) and 95% confidence intervals (CI) comparing any versus no prescriptions for each of the most commonly prescribed medicines, identified from prescription records, were calculated using conditional logistic regression, adjusting for comorbidities. Additional analyses adjusted for smoking use. An association was considered a signal based upon the magnitude of its adjusted OR, p-value and evidence of an exposure-response relationship. Supplementary analyses were undertaken comparing 6 or more prescriptions versus less than 6 for each medicine. Results Overall, 62,109 cases and 276,580 controls were included in the analyses and a total of 5622 medication-cancer associations were studied across the 22 cancer sites. After adjusting for comorbidities 2060 medicine-cancer associations for any prescription had adjusted ORs greater than 1.25 (or less than 0.8), 214 had a corresponding p-value less than or equal to 0.01 and 118 had evidence of an exposure-dose relationship hence meeting the criteria for a signal. Seventy-seven signals were identified after additionally adjusting for smoking. Based upon an exposure of 6 or more prescriptions, there were 118 signals after adjusting for comorbidities and 82 after additionally adjusting for smoking. Conclusions In this study a number of novel associations between medicine and cancer were identified which require further clinical and epidemiological investigation. The majority of medicines were not associated with an altered cancer risk and many identified signals reflected known associations between medicine and cancer.

Genetic polymorphism of miR-218-2 (rs11134527) in cervical cancer: a case-control study in the Bangladeshi women

MicroRNA ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Farhana Nazneen ◽  
Md. Shalahuddin Millat ◽  
Md. Abdul Barek ◽  
Md. Abdul Aziz ◽  
Mohammad Sarowar Uddin ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cancer Patients ◽  
Case Control Study ◽  
Case Control ◽  
Recessive Model ◽  
Cancer Type ◽  
Increased Risk ◽  
Hardy Weinberg Equilibrium ◽  
Control Study ◽  
Healthy Females

Background: The prevalence of Cervical Cancer (CC) is disproportionately higher in developing countries. It is the second most frequent cancer type among Bangladeshi women and the primary cause of morbidity and mortality. However, no previous data reported the association of miR-218-2 gene polymorphisms in Bangladeshi cervical cancer patients. Aim: This case-control study was designed to find the link between the rs11134527 polymorphism in miR-218-2 and CC. Methods: A total of 488 subjects were recruited, comprising 256 cervical cancer patients and 232 healthy females. Genotyping was conducted with the tetra-primer ARMS-PCR technique to detect the association. Results: The results of genotype data showed that rs11134527 obeyed the Hardy-Weinberg equilibrium in both CC cases and controls (P >0.05). Overall, the polymorphism was found to be significantly associated with an increased risk of cervical cancer with AG genotype (AG vs. GG: OR = 2.26, 95% Cl = 1.40-3.66, P = 0.0008), AA genotype (AA vs. GG: OR = 3.64, 95% Cl = 2.17-6.10, P <0.0001), dominant model (AG+AA vs. GG: OR = 2.75, 95% Cl = 1.75-4.31, P <0.0001), recessive model (AA vs. GG+AG: OR = 2.08, 95% Cl = 1.41-3.08, P = 0.0002), and A allele (A vs. G: OR = 1.94, 95% Cl = 1.51-2.51, P <0.0001). All of these correlations remained statistically significant after performing Bonferroni correction (P <0.008). Conclusion: Our study suggests that the rs11134527 polymorphism in the miR-218-2 gene contributes to the susceptibility of CC in Bangladeshi women.

scholarly journals Nested Case-Control Studies With Multiple Measurements: Estimating Marginal Relationships

2021 ◽  
Author(s):  
Joshua N. Sampson ◽  
Paul S. Albert ◽  
Mark P. Purdue
Keyword(s):  
Conditional Logistic Regression ◽  
Case Control ◽  
Case Control Studies ◽  
Robust Variance ◽  
Non Hodgkin Lymphoma ◽  
Multiple Measurements ◽  
Matched Case ◽  
Nested Case Control ◽  
Standard Software ◽  
Single Time Point

Abstract Background: We consider the analysis of nested, matched, case-control studies that have multiple biomarker measurements per individual. We propose a simple approach for estimating the marginal relationship between a biomarker measured at a single time point and the risk of an event. We know of no other standard software package that can perform such analyses while explicitly accounting for the matching. Results: We propose an application of conditional logistic regression (CLR) that can include all measurements and uses a robust variance estimator. We compare our approach to other methods such as performing CLR with only the first measurement, CLR with an average of all measurements, and Generalized Estimating Equations. In simulations, our approach is significantly more powerful than CLR with one measurement or an average of all measurements, and has similar to power to GEE but correctly accounts for the matching. We then apply our approach to the CLUE cohort to show that an increased level of the immune marker sCD27 is associated with non‐Hodgkin lymphoma (NHL) and, by evaluating the strength of the association as a function of time until diagnosis, that the an increased level is likely an effect of the disease as opposed to a cause of the disease. The approach can be implemented by the R function clogitRV available at https://github.com/sampsonj74/clogitRV.Conclusion: We offered an approach and software for analyzing matched case-control studies with multiple measurements. We demonstrated that these methods are accurate, precise, and statistically powerful.

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