Chaffee, Kari G.

Summary The ultimate cause of death for most patients with newly diagnosed chronic lymphocytic leukaemia ( CLL ) and its relationship to co‐morbid health conditions is poorly defined. We conducted a prospective cohort study that systematically followed 1143 patients diagnosed with CLL between June 2002 and November 2014. Comorbid health conditions at the time of CLL diagnosis and their relationship to survival and cause of death were evaluated. Collectively, 1061 (93%) patients had at least one co‐morbid health condition at the time of CLL diagnosis (median number 3). Despite this, 89% of patients had a low‐intermediate Charlson Comorbidity Index score ( CCI ) at diagnosis. After a median follow‐up of 6 years, 225 patients have died. Death was due to CLL progression in 85 (46%) patients, infection in 14 (8%) patients, other cancer in 35 (19%) patients and comorbid health conditions in 50 (27%) patients. Higher CCI score and a greater number of major comorbid health conditions at the time of CLL diagnosis was associated with shorter non‐ CLL specific survival, but not with shorter CLL ‐specific survival on multivariate analysis. In conclusion, CLL and CLL ‐related complications (infections and second cancers) are the overwhelming cause of death in patients with CLL , regardless of CCI score and number of comorbid health conditions at diagnosis.

SummaryCD49d is a surface integrin that is expressed on chronic lymphocytic leukaemia (CLL) cells, and strongly correlates with more aggressive disease. Given its association with cell‐cell adhesion and leucocyte trafficking, we hypothesized that patients with high CD49d expression would experience a clinical course dominated by lymphadenopathy. CD49d expression was measured by flow cytometry and considered positive if expressed by ≥30% of CLL cells. The study included 797 newly diagnosed CLL/small lymphocytic leukaemia patients; 279 (35%) were CD49d positive. CD49d‐positive patients were more likely to present with lymphadenopathy (P < 0·001); a finding that persisted after adjusting for fluorescence in situ hybridisation (FISH) and IGHV mutation status [odds ratio (OR) 2·51; 95% confidence interval (CI) 1·64–3·83; P < 0·001]. Among CLL Rai 0 patients, CD49d positivity was associated with shorter time to development of lymphadenopathy (3·2 years vs not reached, P < 0·01). This association was maintained after adjusting for either FISH [hazard ratio (HR) 2·18; 95% CI 1·25–3·81; P = 0·006) or IGHV status (HR 2·02; 95% CI 1·11–3·69; P = 0·02) individually, but was attenuated when adjusting by both (HR 1·72; 95% CI 0·88–3·38; P = 0·11).These data demonstrate that CD49d‐positive CLL patients experience a disease course dominated by lymphadenopathy. These findings could have implications for therapy selection and disease monitoring.

Abstract Background: Epidemiologic associations of leukocyte telomere length (LTL) and pancreatic ductal adenocarcinoma (PDAC) have been inconsistent owing, in part, to variation in telomere length (TL) assessment across studies. To overcome this limitation and address concerns of potential reverse causation, we used carriage of telomere-related alleles to genetically predict TL and examined its association with PDAC. Methods: A case–control study of 1,500 PDAC cases and 1,500 controls, frequency-matched on age and sex was performed. Eight of nine polymorphisms previously associated with variation in LTL were analyzed. Genetic risk scores (GRS) consisting of the TL-related polymorphisms were computed as the number of long TL alleles carried by an individual scaled to published kilobase pairs of TL associated with each allele. Participants were further categorized on the basis of the number of short TL alleles they carry across all eight SNPs. Associations were examined in additive and dominant models using logistic regression to calculate ORs and 95% confidence intervals (CI). Results: In age- and sex-adjusted models, one short TL allele (rs10936599, T) was associated with reduced risk, whereas another short TL allele (rs2736100, A) was associated with increased risk, with per-allele ORs of 0.89 (95% CI, 0.79–0.99) and 1.13 (95% CI, 1.01–1.24), respectively. No association was observed with GRS or short TL allele counts, and no associations were observed in the dominant models. Conclusions: Findings suggest that genetically predicted short TL is not associated with PDAC risk. Impact: Common genetic determinants of short TL do not appear to influence PDAC risk. Cancer Epidemiol Biomarkers Prev; 26(6); 971–4. ©2017 AACR.

The chronic lymphocytic leukemia International Prognostic Index (CLL‐IPI) combines 5 parameters (age, clinical stage, TP53 status [normal vs. del(17p) and/or TP53 mutation], IGHV mutational status, serum β2‐microglobulin) to predict survival and time‐to‐first‐treatment (TTFT) in CLL patients. We performed an observational study in 337 prospectively collected, Binet stage A patients to validate the ability of the CLL‐IPI to predict TTFT in an independent cohort of early stage CLL patients. The CLL‐IPI score stratified Binet stage A patients into three subgroups with different outcome. Since the CLL‐IPI was originally developed to predict survival, we next investigated the optimal cut‐off score to predict TTFT in Binet stage A patients. Recursive partitioning analysis identified three subsets with scores of 0 (n = 139), 1 (n = 90), and ≥ 2(n = 108). The probability of remaining free from therapy 5 years after diagnosis was 85%, 67% and 46% in these three categories (P < 0.0001.; C‐statistic:c = 0.72; 95% CI:0.58‐0.81). This optimized CLL‐IPI scoring for TTFT was subsequently validated in an independent cohort of Binet A patients from the Mayo Clinic (n = 525). The ability of either original or optimized CLL‐IPI to predict TTFT was equivalent to other prognostic models specifically designed for this endpoint (2011 MDACC score and O‐CLL1 score). Although originally developed to predict suvival, the CLL‐IPI is useful for predicting TTFT in early stage CLL patients. Am. J. Hematol. 91:1090–1095, 2016. © 2016 Wiley Periodicals, Inc.

Abstract Individuals from pancreatic cancer families are at increased risk, not only of pancreatic cancer, but also of melanoma, breast, ovarian, and colon cancers. While some of the increased risk may be due to mutations in high-penetrance genes (i.e., BRCA2, PALB2, ATM, p16/CDKN2A or DNA mismatch repair genes), common genetic variants may also be involved. In a high-risk population of cases with either a family history of pancreatic cancer or early-onset pancreatic cancer (diagnosis before the age of 50 years), we examined the role of genetic variants previously associated with risk of pancreatic, breast, ovarian, or prostate cancer. We genotyped 985 cases (79 early-onset cases, 906 cases with a family history of pancreatic cancer) and 877 controls for 215,389 SNPs using the iSelect Collaborative Oncological Gene-Environment Study (iCOGS) array with custom content. Logistic regression was performed using a log-linear additive model. We replicated several previously reported pancreatic cancer susceptibility loci, including recently identified variants on 2p13.3 and 7p13 (2p13.3, rs1486134: OR = 1.36; 95% CI, 1.13–1.63; P = 9.29 × 10−4; 7p13, rs17688601: OR = 0.76; 95% CI, 0.63–0.93; P = 6.59 × 10−3). For the replicated loci, the magnitude of association observed in these high-risk patients was similar to that observed in studies of unselected patients. In addition to the established pancreatic cancer loci, we also found suggestive evidence of association (P &lt; 5 × 10−5) to pancreatic cancer for SNPs at HDAC9 (7p21.1) and COL6A2 (21q22.3). Even in high-risk populations, common variants influence pancreatic cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 25(7); 1185–91. ©2016 AACR.

Purpose The inclusion of metformin in the treatment arms of cancer clinical trials is based on improved survival that has been demonstrated in retrospective epidemiologic studies; however, unintended biases may exist when analysis is performed by using a conventional Cox proportional hazards regression model with dichotomous ever/never categorization. We examined the impact of metformin exposure definitions, analytical methods, and patient selection on the estimated effect size of metformin exposure on survival in a large cohort of patients with pancreatic ductal adenocarcinoma (PDAC). Patients and Methods Of newly diagnosed patients with PDAC with diabetes, 980 were retrospectively included, and exposure to metformin documented. Median survival was assessed by using Kaplan-Meier and log-rank methods. Hazard ratios (HR) and 95% CIs were computed to compare time-varying covariate analysis with conventional Cox proportional hazards regression analysis. Results Median survival of metformin users versus nonusers was 9.9 versus 8.9 months, respectively. By the time-varying covariate analysis, metformin use was not statistically significantly associated with improved survival (HR, 0.93; 95% CI, 0.81 to1.07; P = .28). There was no evidence of benefit in the subset of patients who were naïve to metformin at the time of PDAC diagnosis (most representative of patients enrolled in clinical trials; HR, 1.01; 95% CI, 0.80 to 1.30; P = .89); however, when the analysis was performed by using the conventional Cox model, an artificial survival benefit of metformin was detected (HR, 0.88; 95% CI, 0.77 to 1.01; P = .08), which suggested biased results from the conventional Cox analysis. Conclusion Our findings did not suggest the benefit of metformin use after patients are diagnosed with PDAC. We highlight the importance of patient selection and appropriate statistical analytical methods when studying medication exposure and cancer survival.