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329 citation(s) found for "Völp, Kirsten".

Abstract P3-06-25: MammaPrint High1/High2 risk class as a biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL
Sanil, Ashish, Chien, Jo, Kaplan, Hank, Albain, Kathy S. , Viscuzi, Rebecca, Moulder, Stacey, Chui, Steven, Styblo, Toncred M., Edmiston, Kirsten K., Northfelt, Donald W. , Haley, Barbara , Flynn, Susan, Buxton, Meredith , Hylton, Nola, Paoloni, Melissa, Symmans, Fraser, Berry, Don, Veer, Laura van ‘t , Wolf, Denise M. , Yau, Christina , Wallace, Anne M. , DeMichele, Angela , Yee, Douglas , Isaacs, Claudine , Boughey, Judy C. , Khan, Qamar J. , Elias, Anthony , Tripathy, Debu , Swigart, Lamorna Brown , Hirst, Gillian L. , Esserman, Laura J. , Berry, Donald A. , Rugo, Hope S. , Olopade, Olufunmilayo I. , Veer, Laura J. van’t

Cancer Research | May 4, 2015 | Volume: 75 | Issue: 9_Supplement | Pages: P3-06-25-P3-06-25

10.1158/1538-7445.sabcs14-p3-06-25 Get It

Abstract Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score <-0.154. MP1/MP2 classification was added to HR and Her2 to define the cancer subtypes used in the I-SPY 2 adaptive randomization engine. HER2- patients were randomized to receive standard chemotherapy or the oral PARP inhibitor veliparib in combination with carboplatin (V/C) and chemotherapy. V/C graduated in the triple-negative (TN) signature, where MP2 was not an eligible signature for graduation. Here, we assess the performance of MP1/MP2 class as a specific biomarker of response to V/C. Methods:115 HER2- patients (V/C: 71 and concurrent controls: 44) were considered in this analysis. We assess association between MP1/MP2 and response in the V/C and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p < 0.05) using a logistic model. This analysis is also performed adjusting for HR status as a covariate. To assess MP1/MP2 in the context of the graduating signature, we added the MP2 patients to the graduating TN subset and evaluated the treatment effect in this ‘biomarker-positive’ group. Our study is exploratory with no claims for generalizability of the data. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). This analysis does not adjust for multiplicities of other biomarkers in the trial but outside this study. Results: In the V/C arm vs. concurrent controls, there were 66 MP1 (V/C: 32, Control: 34) and 49 MP2 patients (V/C: 39, Control: 10), 78% of which are TN. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. V/C (n=71)Control (n=44)MP1 (n=32)MP2 (n=39)MP1 (n=34)MP2 (n=10)TN (n=59)3 / 819 / 303 / 132 / 8HR+HER2- (n=56)1 / 244 / 94 / 210 / 2 The OR between MP1/MP2 risk groups for predicting pCR is 9.71 in the V/C arm (p=6.63E-05), in comparison to an OR of 0.97 in the control arm (p=1). There is a significant biomarker x treatment interaction (p=0.023), which remains upon adjusting for HR status (p= 0.028). Based on the I-SPY 2 Bayesian model, a Phase III trial with 300 MP2 patients has a 95% predictive probability of success. When the MP2 patients are added to the graduating TN subset, the OR associated with V/C is 4.36, which is comparable to that of the TN signature (OR: 4.29), while increasing the prevalence of biomarker-positive patients by ∼10%. Conclusion: In our exploratory analysis, MP2 suggests higher sensitivity to V/C combination therapy relative to controls. This observation has prompted an investigation into the biological mechanisms distinguishing the MP1/MP2 subtype that may account for this specificity. Citation Format: Denise M Wolf, Christina Yau, Ashish Sanil, Jo Chien, Anne Wallace, Angela DeMichele, Hank Kaplan, Doug Yee, Claudine Isaacs, Kathy Albain, Rebecca Viscuzi, Judy Boughey, Stacey Moulder, Steven Chui, Qamar Khan, Toncred Styblo, Kirsten Edmiston, Donald Northfelt, Anthony Elias, Barbara Haley, Debu Tripathy, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, Fraser Symmans, Laura Esserman, Don Berry, Hope Rugo, Olufunmilayo I. Olopade, Laura van 't Veer. MammaPrint High1/High2 risk class as a biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-25.
Abstract CT227: Neratinib plus standard neoadjuvant therapy for high-risk breast cancer: Efficacy results from the I-SPY 2 TRIAL
Park, John W., Liu, Minetta C. , Veer, Laura van ‘t , Hylton, Nola, Symmans, Fraser, Buxton, Meredith , Chien, A. Jo , Wallace, Amy E., Melisko, Michelle , Schwab, Richard B. , Tripathy, Debashish, Kaplan, Hank, Nanda, Rita , Albain, Kathy S. , Moulder, Stacy L. , Edminston, Kirsten, Northfelt, Donald W. , Euhus, David , Khan, Qamar J. , Lyandres, Julia, Sanil, Ashish, Berry, Donald A. , Yee, Douglas , DeMichele, Angela , Veer, Laura J. van’t , Boughey, Judy C. , Hui, Jane Yuet Ching , Elias, Anthony , Lang, Julie E. , Davis, Sarah , Yau, Christina , Esserman, Laura J.

Cancer Research | May 1, 2015 | Volume: 74 | Issue: 19_Supplement | Pages: CT227-CT227

10.1158/1538-7445.am2014-ct227 Get It

Abstract Background: I-SPY 2 is a multicenter, phase II neoadjuvant trial in women with high-risk stage II/III breast cancer using adaptive randomization within biomarker subtypes to evaluate novel agents added to standard chemotherapy. Primary endpoint is pathologic complete response (pCR). Goal is to identify regimens that meet a high Bayesian predictive probability of statistical significance in a neoadjuvant 300-patient phase III trial defined by hormone-receptor (HR), HER2 status, and MammaPrint (MP). Experimental regimens may “graduate” in 1 of 10 signatures, with a maximum of 120 patients. We report efficacy results for neratinib (N). Methods: Tumors ≥2.5cm by clinical exam & ≥2cm by imaging are eligible for screening. MP low risk/HR+/HER2- tumors are ineligible for randomization. Patients receive chemotherapy (paclitaxel qwk x 12, doxorubicin and cyclophosphamide q2-3 wk x 4, T->AC). HER2- pts were randomized to N+T->AC vs. T->AC and HER2+ pts to N+T->AC vs. trastuzumab+T->AC. Analysis is intent-to-treat with pts who switch to non-protocol therapy regarded as non-pCRs. We provide estimated pCR rates (95% Bayesian probability intervals), probabilities of superiority of neratinib over control, and Bayesian predictive probabilities of success in an equally randomized phase III trial. Results: Neratinib met the predictive probability criterion in HR-/HER2+, “graduated”, and accrual ceased [115 N patients (65 HER2+), 78 concurrently randomized controls (22 HER2+)]. The table shows results for all 10 signatures. Two patients (1 N and 1 control) withdrew consent and are not included. Conclusion: I-SPY 2's standing trial mechanism efficiently evaluates agents in biomarker-defined patient subsets. In a modest number of patients, adaptive randomization successfully identified a biomarker signature (HR-/HER2+) for neratinib's further development. All HER2+ and MP+ tumors may also benefit from this regimen, consistent with preclinical data. Evaluation in I-SPY 3, a phase III registration trial, is planned. SignatureEstimated pCR Rate (95% probability interval)Probability NeratinibIs Superior to ControlPredictive Probability of Success in Phase IIINeratinibControlALL32% (28-36%)23% (19%-28%)92%44%HR+23% (18%-28%)17% (11%-22%)81%40%HR-43% (37%-49%)31% (24%-38%)89%53%HER2+39% (33%-45%)23% (15%-30%)95%73%HER2-26% (21%-32%)24% (18%-29%)63%20%MP+*45% (38%-53%)29% (20%-39%)91%66%HR-/HER2-36% (29%-43%)30% (23%-38%)72%34%HR-/HER2+55% (46%-64%)32% (22%-43%)94%78%HR+/HER2+31% (24%-37%)17% (10%-24%)91%65%HR+/HER2-14% (8%-19%)16% (10%-21%)39%12%* MammaPrint 44K Array Low/High score was adjusted to MammaPrint High1 (MP-) or High2 (MP+), using a pre-defined median cut-point of I-SPY 1 participants, who fit the eligibility criteria of I-SPY 2. Citation Format: John W. Park, Minetta C. Liu, Douglas Yee, Angela DeMichele, Laura van 't Veer, Nola Hylton, Fraser Symmans, Meredith B. Buxton, A. Jo Chien, Amy Wallace, Michelle Melisko, Richard Schwab, Judy Boughey, Debashish Tripathy, Hank Kaplan, Rita Nanda, Stephen Chui, Kathy S. Albain, Stacy Moulder, Anthony Elias, Julie E. Lang, Kirsten Edminston, Donald Northfelt, David Euhus, Qamar Khan, Julia Lyandres, Sarah E. Davis, Christina Yau, Ashish Sanil, Laura J. Esserman, Donald A. Berry. Neratinib plus standard neoadjuvant therapy for high-risk breast cancer: Efficacy results from the I-SPY 2 TRIAL. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr CT227. doi:10.1158/1538-7445.AM2014-CT227
Direct medical costs and source of cost differences across the spectrum of cognitive decline: A population‐based study
Leibson, Cynthia L., Long, Kirsten Hall , Ransom, Jeanine E. , Roberts, Rosebud O., Hass, Steven , Duhig, Amy, Smith, Carin Y. , Emerson, Jane A., Petersen, Ronald C. , Pankratz, V. Shane , Smith, Carin Y

Alzheimer's & Dementia | April 9, 2015 | Volume: 11 | Issue: 8 | Pages: 917-932

10.1016/j.jalz.2015.01.007 | PMID 25858682 Get It

Abstract Background Objective cost estimates and source of cost differences are needed across the spectrum of cognition, including cognitively normal (CN), mild cognitive impairment (MCI), newly discovered dementia, and prevalent dementia. Methods Subjects were a subset of the Mayo Clinic Study of Aging stratified‐random sampling of Olmsted County, MN, residents aged 70 to 89 years. A neurologist reviewed provider‐linked medical records to identify prevalent dementia (review date = index). Remaining subjects were invited to participate in prospective clinical/neuropsychological assessments; participants were categorized as CN, MCI, or newly discovered dementia (assessment date = index). Costs for medical services/procedures 1‐year pre‐index (excluding indirect and long‐term care costs) were estimated using line‐item provider‐linked administrative data. We estimated contributions of care‐delivery site and comorbid conditions (including and excluding neuropsychiatric diagnoses) to between‐category cost differences. Results Annual mean medical costs for CN, MCI, newly discovered dementia, and prevalent dementia were $6042, $6784, $9431, $11,678, respectively. Hospital inpatient costs contributed 70% of total costs for prevalent dementia and accounted for differences between CN and both prevalent and newly discovered dementia. Ambulatory costs accounted for differences between CN and MCI. Age‐, sex‐, education‐adjusted differences reached significance for CN versus newly discovered and prevalent dementia and for MCI versus prevalent dementia. After considering all comorbid diagnoses, between‐category differences were reduced (e.g., prevalent dementia minus MCI (from $4842 to $3575); newly discovered dementia minus CN (from $3578 to $711)). Following the exclusion of neuropsychiatric diagnoses from comorbidity adjustment, between‐category differences tended to revert to greater differences. Conclusions Cost estimates did not differ significantly between CN and MCI. Substantial differences between MCI and prevalent dementia reflected high inpatient costs for dementia and appear partly related to co‐occurring mental disorders. Such comparisons can help inform models aimed at identifying where, when, and for which individuals proposed interventions might be cost‐effective.
Cell-type-specific enrichment of risk-associated regulatory elements at ovarian cancer susceptibility loci
Coetzee, Simon G. , Shen, Howard C., Hazelett, Dennis J. , Lawrenson, Kate , Kuchenbaecker, Karoline , Rhie, Suhn K. , Levanon, Keren , Karst, Alison M., Drapkin, Ronny , Ramus, Susan J. , Offit, Kenneth, Chenevix‐Trench, Georgia , Monteiro, Álvaro N.A. , Antoniou, Antonis C. , Freedman, Matthew L., Coetzee, Gerhard A. , Gayther, Simon A. , Antonenkova, Natalia, Bean, Yukie T., Beckmann, Matthias W. , Bisogna, Maria, Bogdanova, Natalia , Brinton, Louise A. , Bruinsma, Fiona , Chang‐Claude, Jenny, Chen, Ann , Chen, Zhihua , Cunningham, Julie M. , Dansonka‐Mieszkowska, Agnieszka , Dicks, Ed , Dörk, Thilo , Eccles, Diana , Easton, Douglas F. , Edwards, Robert P., Eilber, Ursula, Ekici, Arif B. , Fasching, Peter A. , Gao, Yu‐Tang , Giles, Graham G. , Glasspool, Rosalind , Goode, Ellen L. , Grownwald, Jacek, Harrington, Patricia, Harter, Philipp , Hasmad, Hanis Nazihah, Hein, Alexander , Heitz, Florian , Hildebrandt, Michelle A.T., Hillemanns, Peter , Høgdall, Claus , Hosono, Satoyo , Iversen, Edwin S., Jakubowska, Anna , James, Paul A. , Jensen, Allan , Ji, Bu‐Tian , Kjær, Susanne K. , Kelemen, Linda E. , Kellar, Melissa, Kelley, Joseph L., Kiemeney, Lambertus A. , Krakstad, Camilla , Kupryjańczyk, Jolanta , Lambrechts, Diether , Lambrechts, Sandrina, Le, Nhu D. , Lele, Shashi, Leminen, Arto, Lester, Jenny, Levine, Douglas A. , Lissowska, Jolanta , Lu, Karen, Lubiński, Jan , Lundvall, Lene, Massuger, Leon F.A.G. , Matsuo, Keitaro , McGuire, Valerie , McLaughlin, John R., McNeish, Ian, Menon, Usha , Moysich, Kirsten B., Narod, Steven A., Nedergaard, Lotte , Ness, Roberta B., Azmi, Mat Adenan Noor, Odunsi, Kunle , Oršulić, Sandra , Pearce, Celeste Leigh, Pelttari, Liisa M. , Permuth‐Wey, Jennifer, Phelan, Catherine M., Pike, Malcolm C., Rossing, Mary Anne, Rothstein, Joseph H. , Runnebaum, Ingo B., Rzepecka, Iwona K. , Salvesen, Helga B., Schildkraut, Joellen M. , Schwaab, Ira, Sellers, Thomas A. , Shu, Xiao‐Ou, Shvetsov, Yurii B. , Sieh, Weiva , Song, Honglin , Southey, Melissa C. , Sucheston, Lara, Tangen, Ingvild L. , Teo, Soo‐Hwang , Thompson, Pamela J., Timorek, Agnieszka, Tworoger, Shelley S. , Altena, Anne M. van , Nieuwenhuysen, Els Van , Vergote, Ignace , Vierkant, Robert A. , Wang‐Gohrke, Shan , Walsh, Christine , Wentzensen, Nicolas, Whittemore, Alice S. , Wicklund, Kristine G. , Woo, Yin Ling , Wu, Xifeng , Wu, Anna H. , Lu, Karen H. , McNeish, Iain A. , Lambrechts, Diether , Tyrer, Jonathan P. , Couch, Fergus J. , Pharoah, Paul D.P. , Noushmehr, Houtan , Anton‐Culver, Hoda , Baker, Helen H. , Bandera, Elisa V. , Berchuck, Andrew , Bjørge, Line , Brooks‐Wilson, Angela , Bützow, Ralf C. , Campbell, Ian , Carty, Karen , Cook, Linda S. , Cramer, Daniel W. , Cybulski, Cezary , Dennis, Joe , Doherty, Jennifer A. , Bois, Andreas du , Dürst, Matthias , Fridley, Brooke L. , Gentry‐Maharaj, Aleksandra , Goodman, Marc T. , Hildebrandt, Michelle A.T. , Høgdall, Estrid , Karlan, Beth Y. , Lester, Jenny, Liang, Dong , Lu, Karen, McLaughlin, John R., McNeish, Ian, Modugno, Francesmary , Olson, Sara H. , Orlow, Irene , Weber, Rachel Palmieri , Pejovic, Tanja B. , Poole, Elizabeth M. , Risch, Harvey A. , Rosen, Barry P. , Rudolph, Anja , Siddiqui, Nadeem , Terry, Kathryn L. , Wentzensen, Nicolas , Wilkens, Lynne R. , Yang, Hannah , Zheng, Wei , Ziogas, Argyrios , Pelttari, L M , Dörk, Thilo , Lambrechts, Diether , Giles, Graham G , James, Paul , Kiemeney, Lambertus A , Kjaer, Susanne K , McNeish, Iain A , Ramus, Susan J , Teo, Soo H , Tworoger, Shelley S , Hein, Alexander , Hillemanns, Peter , Jensen, Allan , Vierkant, Robert A , Eccles, Diana , Menon, Usha , Lawrenson, Kate , Hazelett, Dennis J , Coetzee, Simon G , Monteiro, Alvaro N , Lissowska, Jolanta , Southey, Melissa C , Glasspool, Rosalind , Matsuo, Keitaro , Heitz, Florian , Jakubowska, Anna , Kupryjanczyk, Jolanta , Lambrechts, Diether , Sieh, Weiva , Ekici, Arif B , Bogdanova, Natalia V , Chenevix-Trench, Georgia , Drapkin, Ronny , Høgdall, Claus K , Lubinski, Jan

Human Molecular Genetics | March 24, 2015 | Volume: 24 | Issue: 13 | Pages: 3595-3607

10.1093/hmg/ddv101 | PMID 25804953 Get It

Women-Specific Factors to Consider in Risk, Diagnosis and Treatment of Cardiovascular Disease
Harvey, Ronée E. , Coffman, Kirsten E. , Miller, Virginia M. , Harvey, Ronée E

Women's Health | March 17, 2015 | Volume: 11 | Issue: 2 | Pages: 239-257

10.2217/whe.14.64 | PMID 25776297 Get It

In the era of individualized medicine, gaps in knowledge remain about sex-specific risk factors, diagnostic and treatment options that might reduce mortality from cardiovascular disease (CVD) and improve outcomes for both women and men. In this review, contributions of biological mechanisms involving the sex chromosomes and the sex hormones on the cardiovascular system will be discussed in relationship to the female-specific risk factors for CVD: hypertensive disorders of pregnancy, menopause and use of hormonal therapies for contraception and menopausal symptoms. Additionally, sex-specific factors to consider in the differential diagnosis and treatment of four prevalent CVDs (hypertension, stroke, coronary artery disease and congestive heart failure) will be reviewed with emphasis on areas where additional research is needed.
The Neoadjuvant Model Is Still the Future for Drug Development in Breast Cancer
DeMichele, Angela, Yee, Douglas , Berry, Donald A. , Albain, Kathy S. , Benz, Christopher C. , Buxton, Meredith , Chia, Stephen , Chien, A. Jo , Clark, Amy S. , Edmiston, Kirsten K., Forero‐Torres, Andres , Haddad, Tufia C. , Haley, Barbara , Haluska, Paul , Korde, Larissa A. , Leyland‐Jones, Brian , Liu, Minetta C. , Melisko, Michelle , Minton, Susan, Moulder, Stacy L. , Nanda, Rita , Olopade, Olufunmilayo I. , Paoloni, Melissa, Park, John W., Parker, Barbara A. , Perlmutter, Jane , Petricoin, Emanuel F. , Symmans, Fraser, Tripathy, Debasish , Veer, Laura J. van’t , Viscusi, Rebecca K., Symmans, W. Fraser , Boughey, Judy, Boughey, Judy C. , Hui, Jane Yuet Ching , Elias, Anthony , Hylton, Nola M. , Isaacs, Claudine , Kaplan, Henry G. , Rugo, Hope S. , Wallace, Anne M. , Wolf, Denise M. , Yau, Christina , Esserman, Laura J. , Olopade, Olufunmilayo I , Symmans, W Fraser , Yee, Douglas

Clinical Cancer Research | February 26, 2015 | Volume: 21 | Issue: 13 | Pages: 2911-2915

10.1158/1078-0432.ccr-14-1760 | PMID 25712686 Get It

AbstractThe many improvements in breast cancer therapy in recent years have so lowered rates of recurrence that it is now difficult or impossible to conduct adequately powered adjuvant clinical trials. Given the many new drugs and potential synergistic combinations, the neoadjuvant approach has been used to test benefit of drug combinations in clinical trials of primary breast cancer. A recent FDA-led meta-analysis showed that pathologic complete response (pCR) predicts disease-free survival (DFS) within patients who have specific breast cancer subtypes. This meta-analysis motivated the FDA's draft guidance for using pCR as a surrogate endpoint in accelerated drug approval. Using pCR as a registration endpoint was challenged at ASCO 2014 Annual Meeting with the presentation of ALTTO, an adjuvant trial in HER2-positive breast cancer that showed a nonsignificant reduction in DFS hazard rate for adding lapatinib, a HER-family tyrosine kinase inhibitor, to trastuzumab and chemotherapy. This conclusion seemed to be inconsistent with the results of NeoALTTO, a neoadjuvant trial that found a statistical improvement in pCR rate for the identical lapatinib-containing regimen. We address differences in the two trials that may account for discordant conclusions. However, we use the FDA meta-analysis to show that there is no discordance at all between the observed pCR difference in NeoALTTO and the observed HR in ALTTO. This underscores the importance of appropriately modeling the two endpoints when designing clinical trials. The I-SPY 2/3 neoadjuvant trials exemplify this approach. Clin Cancer Res; 21(13); 2911–5. ©2015 AACR.
Not all IGHV3-21 chronic lymphocytic leukemias are equal: prognostic considerations
Agathangelidis, Andreas , Hadzidimitriou, Anastasia , Sutton, Lesley-Ann, Minga, Eva, Scarfò, Lydia , Davis, Zadie , Yan, Xiao‐Jie , Plevová, Karla , Sandberg, Yorick , Vojdeman, Fie Juhl , Boudjogra, Myriam, Τζένου, Τατιάνα , Chatzouli, Maria, Chu, Charles C. , Veronese, Silvio , Gardiner, Anne, Mansouri, Larry, Smedby, Karin E. , Pedersen, Lone Bredo , Moreno, Denis, Lom, Kirsten van, Giudicelli, Véronique , Francová, Hana Skuhrová, Nguyen‐Khac, Florence , Juliusson, Gunnar , Anagnostopoulos, Αchilles , Lefranc, Marie‐Paule , Facco, Monica , Trentin, Livio , Catherwood, Mark , Montillo, Marco , Geisler, Christian H., Pospı́šilová, Šárka , Oscier, David , Jelinek, Diane F., Darzentas, Nikos , Belessi, Chrysoula, Davi, Frédéric , Ghia, Paolo , Rosenquist, Richard , Σταματόπουλος, Κώστας , Baliakas, Panagiotis , Tsanousa, Athina , Shanafelt, Tait D. , Panagiotidis, Panagiotis T. , Angelis, Lefteris , Langerak, Anton W. , Chiorazzi, Nicholas , Ghia, Paolo , Rosenquist, Richard

Blood | January 29, 2015 | Volume: 125 | Issue: 5 | Pages: 856-859

10.1182/blood-2014-09-600874 | PMID 25634617 Get It

Key Points CLL stereotyped subset #2 (IGHV3-21/IGLV3-21) is uniformly aggressive independently of somatic hypermutation status. The prognosis for non–subset #2/IGHV3-21 CLL resembles that of the remaining CLL cases with similar somatic hypermutation status.
Stratification of hepatocellular carcinoma risk in primary biliary cirrhosis: a multicentre international study
Lammers, Willem J. , Buuren, Henk R. van , Parés, Albert , Floreani, Annarosa , Janssen, Harry L.A. , Invernizzi, Pietro , Battezzati, Pier Maria , Ponsioen, Cyriel Y. , Poupon, Raoul , Mayo, Marlyn J. , Burroughs, Andrew K. , Nevens, Frederik , Lleò, Ana , Caballería, Llorenç , Lindor, Keith D. , Hirschfield, Gideon M. , Bruns, Tony , Boonstra, Kirsten , Trivedi, Palak Jitendrakumar , Corpechot, Christophe , Mason, Andrew L. , Kowdley, Kris V. , Hansen, Bettina E. , Bruns, Tony , Invernizzi, Pietro , Hirschfield, Gideon M

Gut | January 8, 2015 | Volume: 65 | Issue: 2 | Pages: 321-329

10.1136/gutjnl-2014-308351 | PMID 25567117 Get It

Objective Hepatocellular carcinoma (HCC) is an infrequent yet critical event in primary biliary cirrhosis (PBC); however, predictive tools remain ill-defined. Our objective was to identify candidate risk factors for HCC development in patients with PBC. Design Risk factor analysis was performed in over 15 centres from North America and Europe spanning >40 years observation period using Cox proportional hazards assumptions, logistic regression, and Kaplan-Meier estimates. Results Of 4565 patients with PBC 123 developed HCC, yielding an incidence rate (IR) of 3.4 cases/1000 patient-years. HCC was significantly more common in men (p<0.0001), and on univariate analysis factors at PBC diagnosis associated with future HCC development were male sex (unadjusted HR 2.91, p<0.0001), elevated serum aspartate transaminase (HR 1.24, p<0.0001), advanced disease (HR 2.72, p=0.022), thrombocytopenia (HR 1.65, p<0.0001), and hepatic decompensation (HR 9.89, p<0.0001). As such, non-treatment with ursodeoxycholic acid itself was not associated with cancer development; however, 12-month stratification by biochemical non-response (Paris-I criteria) associated significantly with future risk of HCC (HR 4.52, p<0.0001; IR 6.6 vs 1.4, p<0.0001). Non-response predicted future risk in patients with early stage disease (IR 4.7 vs 1.2, p=0.005), advanced disease (HR 2.79, p=0.02; IR 11.2 vs 4.4, p=0.033), and when restricting the analysis to only male patients (HR 4.44, p<0.001; IR 18.2 vs 5.4, p<0.001). On multivariable analysis biochemical non-response remained the most significant factor predictive of future HCC risk (adjusted HR 3.44, p<0.0001). Conclusions This uniquely powered, internationally representative cohort robustly demonstrates that 12-month biochemical non-response is associated with increased future risk of developing HCC in PBC. Such risk stratification is relevant to patient care and development of new therapies.
Frailty in childhood cancer survivors
Ness, Kirsten K. , Armstrong, Gregory T. , Kundu, Mondira , Wilson, Carmen L. , Tchkonia, Tamar , Kirkland, James L. , Tchkonia, T , Ness, Kirsten K

Cancer | December 19, 2014 | Volume: 121 | Issue: 10 | Pages: 1540-1547

10.1002/cncr.29211 | PMID 25529481 Get It

Young adult childhood cancer survivors are at an increased risk of frailty, a physiologic phenotype typically found among older adults. This phenotype is associated with new‐onset chronic health conditions and mortality among both older adults and childhood cancer survivors. Mounting evidence suggests that poor fitness, muscular weakness, and cognitive decline are common among adults treated for childhood malignancies, and that risk factors for these outcomes are not limited to those treated with cranial radiation. Although the pathobiology of this phenotype is not known, early cellular senescence, sterile inflammation, and mitochondrial dysfunction in response to initial cancer or treatment‐related insults are hypothesized to play a role. To the authors' knowledge, interventions to prevent or remediate frailty among childhood cancer survivors have not been tested to date. Pharmaceutical, nutraceutical, and lifestyle interventions have demonstrated some promise. Cancer 2015;121:1540–1547. © 2014 American Cancer Society.