Association Between Total Cell Free DNA and SARS-CoV-2 In Kidney Transplant Patients: A Preliminary Study.

BACKGROUND: Kidney transplant (KT) recipients are at high risk for developing severe COVID-19. Lowering immunosuppression levels in KT recipients with COVID-19 encourages native immune responses but can raise the risk of rejection. Donor-derived cell-free DNA (dd-cfDNA), reported as a fraction of total cfDNA, is a proven biomarker for KT rejection. Total cfDNA levels are elevated in patients with COVID-19, which may depress dd-cfDNA fractions, potentially leading to missed rejections. METHODS: A retrospective analysis of 29 KT recipients hospitalized with COVID-19 between April and November 2020 examined total and dd-cfDNA levels. Blood samples were collected after onset of COVID-19, with follow-up samples collected from a subset of patients, when infection had likely subsided. RESULTS: After COVID-19 diagnosis, the median total cfDNA level was elevated (7.9 multiples of median [MoM]). A significant decrease in total cfDNA levels was observed between the first and second time points (6.2 MoM, 1.0 MoM; P <001). A significant positive association was identified between total cfDNA levels and COVID-19 severity (P = .02; R2 = .19). Two patients with biopsy-proven acute cellular rejection had dd-cfDNA fractions below the 1% cutoff for rejection (0.20% and 0.78%), with elevated total cfDNA levels of 7.9 MoM and 41.8 MoM, respectively. CONCLUSIONS: In this preliminary study, total cfDNA levels were elevated in KT patients with COVID-19, subsiding after resolution of infection. High total cfDNA levels may confound dd-cfDNA results, leading to failure to identify rejection. Considering total cfDNA levels is important in interpretation of dd-cfDNA tests for assessment of rejection in KT patients with COVID-19 or other infection.

A novel donor-derived cell-free DNA assay for the detection of acute rejection in heart transplantation.

BACKGROUND: Endomyocardial biopsy (EMB), the reference surveillance test for acute rejection (AR) in heart transplant (HTx) recipients, is invasive, costly, and shows significant interobserver variability. Recent studies indicate that donor-derived cell-free DNA (dd-cfDNA), obtained non-invasively from blood, is associated with AR and could reduce the frequency of EMB surveillance. The aim of this study was to examine the performance characteristics of a novel test for detecting AR in adult HTx recipients. METHODS: Plasma samples with contemporaneous EMBs were obtained from HTx recipients. A clinically available SNP-based massively multiplexed-PCR dd-cfDNA assay was used to measure dd-cfDNA fraction. dd-cfDNA fractions were compared with EMB-defined rejection status and test performance was assessed by constructing ROC curves and calculating accuracy measures. RESULTS: A total of 811 samples from 223 patients with dd-cfDNA testing and contemporaneous EMB were eligible for the study. dd-cfDNA fraction was significantly higher in AR (median 0.58%, IQR, 0.13%-1.68%) compared to non-AR (median 0.04%, IQR, 0.01%-0.11%, pc < 0.001). ROC analysis produced an area under the curve (AUC-ROC) of 0.86 (95% CI, 0.77-0.96). Defining samples with dd-cfDNA fraction ≥0.15% as AR yielded 78.5% sensitivity (95% CI, 60.7%-96.3%) and 76.9% specificity (95% CI, 71.1%-82.7%). Positive and negative predictive values were 25.1% (95% CI, 18.8%-31.5%) and 97.3% (95% CI, 95.1%-99.5%) respectively, calculated using the cohort AR prevalence of 9.0% (95% CI, 5.3%-12.8%) with adjustment for repeat samples. CONCLUSIONS: This novel dd-cfDNA test detects AR in HTx recipients with good accuracy and holds promise as a noninvasive test for AR in HTx recipients.

Clinical Validation of a Plasma Donor-derived Cell-free DNA Assay to Detect Allograft Rejection and Injury in Lung Transplant.

Background: Lung transplant patients are vulnerable to various forms of allograft injury, whether from acute rejection (AR) (encompassing acute cellular rejection [ACR] and antibody-mediated rejection [AMR]), chronic lung allograft dysfunction (CLAD), or infection (INFXN). Previous research indicates that donor-derived cell-free DNA (dd-cfDNA) is a promising noninvasive biomarker for the detection of AR and allograft injury. Our aim was to validate a clinical plasma dd-cfDNA assay for detection of AR and other allograft injury and to confirm and expand on dd-cfDNA and allograft injury associations observed in previous studies. Methods: We measured dd-cfDNA fraction using a novel single-nucleotide polymorphism-based assay in prospectively collected plasma samples paired with clinical-pathologic diagnoses. dd-cfDNA fraction was compared across clinical-pathologic cohorts: stable, ACR, AMR, isolated lymphocytic bronchiolitis, CLAD/neutrophilic-responsive allograft dysfunction (NRAD), and INFXN. Performance characteristics were calculated for AR and combined allograft injury (AR + CLAD/NRAD + INFXN) versus the stable cohort. Results: The study included 195 samples from 103 patients. Median dd-cfDNA fraction was significantly higher for ACR (1.43%, interquartile range [IQR]: 0.67%-2.32%, P = 5 × 10-6), AMR (2.50%, IQR: 2.06%-3.79%, P = 2 × 10-5), INFXN (0.74%, IQR: 0.46%-1.38%, P = 0.02), and CLAD/NRAD (1.60%, IQR: 0.57%-2.60%, P = 1.4 × 10-4) versus the stable cohort. Area under the receiver operator characteristic curve for AR versus stable was 0.91 (95% confidence interval [CI]: 0.83-0.98). Using a ≥1% dd-cfDNA fraction threshold, sensitivity for AR was 89.1% (95% CI: 76.2%-100.0%), specificity 82.9% (95% CI: 73.3%-92.4%), positive predictive value, 51.9% (95% CI: 37.5%-66.3%), and negative predictive value, 97.3% (95% CI: 94.3%-100%). For combined allograft injury area under the receiver operator characteristic curve was 0.76 (95% CI: 0.66-0.85), sensitivity 59.9% (95% CI: 46.0%-73.9%), specificity 83.9% (95% CI: 74.1%-93.7%), positive predictive value, 43.6% (95% CI: 27.6%-59.6%), and negative predictive value, 91.0% (95% CI: 87.9%-94.0%). Conclusions: These results indicate that our dd-cfDNA assay detects AR and other allograft injury. dd-cfDNA monitoring, accompanied by standard clinical assessments, represents a valuable precision tool to support lung transplant health and is appropriate for further assessment in a prospective randomized-controlled study.

Impact of Circulating Tumor DNA-Based Detection of Molecular Residual Disease on the Conduct and Design of Clinical Trials for Solid Tumors.

PURPOSE: Earlier detection of cancer recurrence using circulating tumor DNA (ctDNA) to detect molecular residual disease (MRD) has the potential to dramatically affect cancer management. We review evidence supporting the use of ctDNA as a biomarker for detection of MRD and highlight the potential impact that ctDNA testing could have on the conduct of clinical trials. METHODS: We searched the literature using MEDLINE (via PubMed) for articles from January 1, 2000, focusing on studies that assessed ctDNA as a predictor of cancer recurrence. Broadly focused searches on ctDNA and cancer were also performed to provide additional background information. www.clinialtrials.gov was searched to identify trials that incorporate ctDNA testing. RESULTS: Numerous studies across different cancer types indicate that ctDNA-based MRD detection predicts recurrence with high sensitivity and specificity, and with lead times that precede standard imaging by up to 12 months. Recently, ctDNA testing has started being used to enroll MRD-positive patients at high risk of recurrence into trials, promising gains in statistical power that allow clinical utility to be demonstrated with smaller cohorts. Trials where ctDNA testing based-MRD detection is used to stratify patients into low or high-risk categories for treatment assignment are also ongoing. In addition, there is increasing evidence supporting the use of ctDNA dynamics or clearance as a surrogate end point, which could significantly reduce trial duration. CONCLUSION: ctDNA-based trial enrichment across many cancers seems likely to become increasingly common for cost- and time-reduction benefits. Trial efficiency could also benefit from using ctDNA as a surrogate end point, leading to accelerated approval of new therapeutics. A clear demonstration of efficacy from trials that use ctDNA-based MRD detection to assign treatment could transform clinical practice.

Incorporation of Donor-derived Cell-free DNA Into Clinical Practice for Renal Allograft Management.

BACKGROUND: Donor-derived cell-free DNA (dd-cfDNA) in plasma is an established noninvasive biomarker for allograft injury and rejection. A single-nucleotide polymorphism (SNP)-based massively multiplexed polymerase chain reaction methodology can be used to quantify dd-cfDNA in kidney transplant recipients. In this study we describe our clinical experience in using a SNP-based dd-cfDNA assay for the management of active rejection in renal transplant recipients. METHODS: To assess the clinical utility of a clinically available SNP-based massively multiplexed polymerase chain reaction dd-cfDNA assay, we analyzed biopsy data contemporaneous to dd-cfDNA results at 33 participating clinics and calculated the rate of rejection in dd-cfDNA-matched biopsy results. RESULTS: A total of 1347 dd-cfDNA test samples from 879 patients were accessioned from October 3, 2019, to November 2, 2020. The dd-cfDNA testing classified 25.2% (340/1347) of samples as high-risk (dd-cfDNA fraction ≥ 1%). Clinical follow-up was available for 32.1% (109/340) of the high-risk results, which included samples from 28 patients with definitive biopsy results within 2 weeks of dd-cfDNA testing. Pathology reports indicated a 64% (18/28) rate of active rejection in biopsy result-matched samples. Total cfDNA measurements indicated a skewed distribution and a correlation with dd-cfDNA-derived patient risk classification. CONCLUSIONS: This is the first report showing the impact of dd-cfDNA on patient management in a multicenter real-world clinical cohort. The data indicate that incorporating dd-cfDNA testing into practice may improve physician decision making regarding renal allograft recipients.

Sensitive tumour detection and classification using plasma cell-free DNA methylomes.

The use of liquid biopsies for cancer detection and management is rapidly gaining prominence1. Current methods for the detection of circulating tumour DNA involve sequencing somatic mutations using cell-free DNA, but the sensitivity of these methods may be low among patients with early-stage cancer given the limited number of recurrent mutations2-5. By contrast, large-scale epigenetic alterations-which are tissue- and cancer-type specific-are not similarly constrained6 and therefore potentially have greater ability to detect and classify cancers in patients with early-stage disease. Here we develop a sensitive, immunoprecipitation-based protocol to analyse the methylome of small quantities of circulating cell-free DNA, and demonstrate the ability to detect large-scale DNA methylation changes that are enriched for tumour-specific patterns. We also demonstrate robust performance in cancer detection and classification across an extensive collection of plasma samples from several tumour types. This work sets the stage to establish biomarkers for the minimally invasive detection, interception and classification of early-stage cancers based on plasma cell-free DNA methylation patterns.

Alcohol and lung cancer risk among never smokers: A pooled analysis from the international lung cancer consortium and the SYNERGY study.

It is not clear whether alcohol consumption is associated with lung cancer risk. The relationship is likely confounded by smoking, complicating the interpretation of previous studies. We examined the association of alcohol consumption and lung cancer risk in a large pooled international sample, minimizing potential confounding of tobacco consumption by restricting analyses to never smokers. Our study included 22 case-control and cohort studies with a total of 2548 never-smoking lung cancer patients and 9362 never-smoking controls from North America, Europe and Asia within the International Lung Cancer Consortium (ILCCO) and SYNERGY Consortium. Alcohol consumption was categorized into amounts consumed (grams per day) and also modelled as a continuous variable using restricted cubic splines for potential non-linearity. Analyses by histologic sub-type were included. Associations by type of alcohol consumed (wine, beer and liquor) were also investigated. Alcohol consumption was inversely associated with lung cancer risk with evidence most strongly supporting lower risk for light and moderate drinkers relative to non-drinkers (>0-4.9 g per day: OR = 0.80, 95% CI = 0.70-0.90; 5-9.9 g per day: OR = 0.82, 95% CI = 0.69-0.99; 10-19.9 g per day: OR = 0.79, 95% CI = 0.65-0.96). Inverse associations were found for consumption of wine and liquor, but not beer. The results indicate that alcohol consumption is inversely associated with lung cancer risk, particularly among subjects with low to moderate consumption levels, and among wine and liquor drinkers, but not beer drinkers. Although our results should have no relevant bias from the confounding effect of smoking we cannot preclude that confounding by other factors contributed to the observed associations. Confounding in relation to the non-drinker reference category may be of particular importance.

Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations.

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR.

META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies.

INTRODUCTION: Gene-set analysis (GSA) methods are used as complementary approaches to genome-wide association studies (GWASs). The single marker association estimates of a predefined set of genes are either contrasted with those of all remaining genes or with a null non-associated background. To pool the p-values from several GSAs, it is important to take into account the concordance of the observed patterns resulting from single marker association point estimates across any given gene set. Here we propose an enhanced version of Fisher's inverse χ2-method META-GSA, however weighting each study to account for imperfect correlation between association patterns. SIMULATION AND POWER: We investigated the performance of META-GSA by simulating GWASs with 500 cases and 500 controls at 100 diallelic markers in 20 different scenarios, simulating different relative risks between 1 and 1.5 in gene sets of 10 genes. Wilcoxon's rank sum test was applied as GSA for each study. We found that META-GSA has greater power to discover truly associated gene sets than simple pooling of the p-values, by e.g. 59% versus 37%, when the true relative risk for 5 of 10 genes was assume to be 1.5. Under the null hypothesis of no difference in the true association pattern between the gene set of interest and the set of remaining genes, the results of both approaches are almost uncorrelated. We recommend not relying on p-values alone when combining the results of independent GSAs. APPLICATION: We applied META-GSA to pool the results of four case-control GWASs of lung cancer risk (Central European Study and Toronto/Lunenfeld-Tanenbaum Research Institute Study; German Lung Cancer Study and MD Anderson Cancer Center Study), which had already been analyzed separately with four different GSA methods (EASE; SLAT, mSUMSTAT and GenGen). This application revealed the pathway GO0015291 "transmembrane transporter activity" as significantly enriched with associated genes (GSA-method: EASE, p = 0.0315 corrected for multiple testing). Similar results were found for GO0015464 "acetylcholine receptor activity" but only when not corrected for multiple testing (all GSA-methods applied; p ≈ 0.02).

Identification of shared and unique susceptibility pathways among cancers of the lung, breast, and prostate from genome-wide association studies and tissue-specific protein interactions.

Results from genome-wide association studies (GWAS) have indicated that strong single-gene effects are the exception, not the rule, for most diseases. We assessed the joint effects of germline genetic variations through a pathway-based approach that considers the tissue-specific contexts of GWAS findings. From GWAS meta-analyses of lung cancer (12 160 cases/16 838 controls), breast cancer (15 748 cases/18 084 controls) and prostate cancer (14 160 cases/12 724 controls) in individuals of European ancestry, we determined the tissue-specific interaction networks of proteins expressed from genes that are likely to be affected by disease-associated variants. Reactome pathways exhibiting enrichment of proteins from each network were compared across the cancers. Our results show that pathways associated with all three cancers tend to be broad cellular processes required for growth and survival. Significant examples include the nerve growth factor (P = 7.86 × 10(-33)), epidermal growth factor (P = 1.18 × 10(-31)) and fibroblast growth factor (P = 2.47 × 10(-31)) signaling pathways. However, within these shared pathways, the genes that influence risk largely differ by cancer. Pathways found to be unique for a single cancer focus on more specific cellular functions, such as interleukin signaling in lung cancer (P = 1.69 × 10(-15)), apoptosis initiation by Bad in breast cancer (P = 3.14 × 10(-9)) and cellular responses to hypoxia in prostate cancer (P = 2.14 × 10(-9)). We present the largest comparative cross-cancer pathway analysis of GWAS to date. Our approach can also be applied to the study of inherited mechanisms underlying risk across multiple diseases in general.

A two-dimensional pooling strategy for rare variant detection on next-generation sequencing platforms.

We describe a method for pooling and sequencing DNA from a large number of individual samples while preserving information regarding sample identity. DNA from 576 individuals was arranged into four 12 row by 12 column matrices and then pooled by row and by column resulting in 96 total pools with 12 individuals in each pool. Pooling of DNA was carried out in a two-dimensional fashion, such that DNA from each individual is present in exactly one row pool and exactly one column pool. By considering the variants observed in the rows and columns of a matrix we are able to trace rare variants back to the specific individuals that carry them. The pooled DNA samples were enriched over a 250 kb region previously identified by GWAS to significantly predispose individuals to lung cancer. All 96 pools (12 row and 12 column pools from 4 matrices) were barcoded and sequenced on an Illumina HiSeq 2000 instrument with an average depth of coverage greater than 4,000×. Verification based on Ion PGM sequencing confirmed the presence of 91.4% of confidently classified SNVs assayed. In this way, each individual sample is sequenced in multiple pools providing more accurate variant calling than a single pool or a multiplexed approach. This provides a powerful method for rare variant detection in regions of interest at a reduced cost to the researcher.

Comparison of pathway analysis approaches using lung cancer GWAS data sets.

Pathway analysis has been proposed as a complement to single SNP analyses in GWAS. This study compared pathway analysis methods using two lung cancer GWAS data sets based on four studies: one a combined data set from Central Europe and Toronto (CETO); the other a combined data set from Germany and MD Anderson (GRMD). We searched the literature for pathway analysis methods that were widely used, representative of other methods, and had available software for performing analysis. We selected the programs EASE, which uses a modified Fishers Exact calculation to test for pathway associations, GenGen (a version of Gene Set Enrichment Analysis (GSEA)), which uses a Kolmogorov-Smirnov-like running sum statistic as the test statistic, and SLAT, which uses a p-value combination approach. We also included a modified version of the SUMSTAT method (mSUMSTAT), which tests for association by averaging χ(2) statistics from genotype association tests. There were nearly 18000 genes available for analysis, following mapping of more than 300,000 SNPs from each data set. These were mapped to 421 GO level 4 gene sets for pathway analysis. Among the methods designed to be robust to biases related to gene size and pathway SNP correlation (GenGen, mSUMSTAT and SLAT), the mSUMSTAT approach identified the most significant pathways (8 in CETO and 1 in GRMD). This included a highly plausible association for the acetylcholine receptor activity pathway in both CETO (FDR≤0.001) and GRMD (FDR = 0.009), although two strong association signals at a single gene cluster (CHRNA3-CHRNA5-CHRNB4) drive this result, complicating its interpretation. Few other replicated associations were found using any of these methods. Difficulty in replicating associations hindered our comparison, but results suggest mSUMSTAT has advantages over the other approaches, and may be a useful pathway analysis tool to use alongside other methods such as the commonly used GSEA (GenGen) approach.

Family-based association study of IGF1 microsatellites and height, weight, and body mass index.

Height, weight, and body mass index (BMI) are partly heritable, known to be associated with chronic diseases, and are linked to circulating insulin-like growth factor I (IGF-I) concentrations. IGF-I concentrations are also partly heritable and thus genetic variation at IGF1 could influence height, weight, BMI and the risk of developing chronic diseases. Our objective was to examine the association of genetic variation at IGF1 with height, weight and BMI using a sample of premenopausal women. A family-based study design was used to investigate the association of three IGF1 CA repeat variants at 5' (5'CA), intron 2 (In2CA) and 3' (3'CA) with these anthropometric measures. We analyzed the data for 827 families of different sizes and configurations, which included 1520 premenopausal women. Nominally significant associations (P

Family-based genetic association study of insulin-like growth factor I microsatellite markers and premenopausal breast cancer risk.

Several studies suggest that higher circulating insulin-like growth factor I (IGF-I) levels are associated with premenopausal breast cancer risk. Breast cancer risk and circulating IGF-I concentration appear to be partly heritable, thus genetic variation at IGF1 could influence IGF-I levels and breast cancer risk. We investigated the association of IGF1 CA repeat variants with premenopausal breast cancer risk using a family-based design. The study sample included 840 families from the Ontario Familial Breast Cancer Registry (OFBCR) and the Australian Breast Cancer Family Registry (ABCFR). Three CA repeat variants, at 5', 3', and in intron 2 were genotyped (5'CA, 3'CA, In2CA). We found several nominally significant associations. The 5'CA-21 allele (P = 0.03) and In2CA-212 allele (P = 0.04) were associated with lower risk, and the In2CA-216 allele with higher risk (P = 0.04) for the combined ABCFR-OFBCR. These associations were not significant after taking into account multiple comparisons. In2CA-216 was more strongly associated with risk when we used a recessive instead of an additive model (P = 0.01). 5'CA alleles of repeat length 18-20 were associated with higher risk (P = 0.02), and 5'CA alleles of >20 repeats were associated with lower risk (P = 0.01). These associations were significant in the OFBCR (In2CA-216 recessive, P = 0.02; 5'CA 18-20 and >20 allele grouping, P = 0.01) but not strongly supported by the ABCFR (In2CA-216 recessive, P = 0.14; 5'CA 18-20, P = 0.25; 5'CA >20, P = 0.20). The associations we found could be due to chance as many comparisons were made. Our results do not strongly support an association between these IGF1 variants and breast cancer risk.

Association between IGF1 CA microsatellites and mammographic density, anthropometric measures, and circulating IGF-I levels in premenopausal Caucasian women.

BACKGROUND: Results from several studies indicate that mammographic density, a strong risk factor for breast cancer, is greater in premenopausal women with higher circulating IGF-I levels. Both mammographic density and circulating IGF-I levels appear to be partly heritable traits. We hypothesized that in premenopausal women, IGF1 variants are associated with circulating IGF-I concentration, which in turn influences variation in breast density. Therefore, we examined the association of IGF1 polymorphisms with circulating IGF-I levels and mammographic density. METHODS: Percentage density, amounts of dense and non-dense (fat) tissue, IGF-I levels, and BMI were measured in 163 premenopausal women. Three CA repeat polymorphisms were genotyped, one each at the 5' and 3' ends of IGF1 and one in intron 2. RESULTS: The number of 19 alleles at the 5' polymorphism was associated with lower circulating levels of IGF-I (P = 0.02), whereas the number of 185 alleles at the 3' polymorphism was associated with higher percentage density (P = 0.03) and a smaller amount of non-dense tissue (P = 0.02). The strength of the effect of the 185 allele at 3' on percentage density was greatly reduced and statistical significance lost when BMI was included in regression models. CONCLUSIONS: Our results suggest an association between the number of 185 alleles at 3' with percentage density. This association appears to be mediated by body composition and particularly body fat, as indicated by the association of 3' IGF1 genotype with non-dense (fat) tissue and the mediating effect of BMI on the association of 3' genotype with percentage density.

Comparison of papanicolaou (Pap) test rates across Ontario and factors associated with cervical screening.

BACKGROUND: Cervical cancer remains a significant yet preventable disease despite the widespread availability of Pap test screening, which detects cervical cancer and its precursor lesions. The aims of this study were to: i) estimate and compare age- and hysterectomy-adjusted Pap test rates across the 37 Ontario public health units (PHUs), and ii) explore the association between several factors and Pap test rates (at the ecological level). METHODS: Cytobase, an Ontario Pap test registry, captures more than 80% of all Pap tests in Ontario. Cytobase was used to determine Pap test rates adjusted for age, hysterectomy and Cytobase coverage for the year 2001. Multiple linear regression analyses were used to evaluate the relationship between Pap test rates and various factors at an ecological level, RESULTS: Age-, hysterectomy- and Cytobase-adjusted one-year Pap rates ranged from 11.6% to 73.9% among PHUs. The overall rate for Ontario was 40.7%. Multivariate analyses indicated that the presence of a teaching hospital was associated with higher Pap test rates. CONCLUSION: One-year Pap test rates varied greatly across the 37 public health units in Ontario. Pap test rates determined using Cytobase were lower than self-reported rates obtained from the Canadian Community Health Survey, possibly due to "over-reporting". In general, women were not screened as frequently as recommended by the Ontario Cervical Screening Program. A positive association was observed between Pap test rates and the presence of a teaching hospital. Data quality issues limit the ability to monitor cervical screening. A provincial registry would address these issues.