Citations

Rituximab improves survival in follicular lymphoma (FL), but is considerably more expensive than conventional chemotherapy. We estimated the total direct medical costs, cumulative survival, and cost-effectiveness of adding rituximab to first-line chemotherapy for FL, based on a single source of data representing routine practice in the elderly. Using surveillance, epidemiology, and end results (SEER) registry data plus Medicare claims, we identified 1,117 FL patients who received first-line CHOP (cyclophosphamide (C), doxorubicin, vincristine (V), and prednisone (P)) or CVP +/−rituximab. Multivariate regression was used to estimate adjusted cumulative cost and survival differences between the two groups over four years after beginning treatment. The median age was 73 years (minimum 66 years), 56% had stage III-IV disease, and 67% received rituximab. Adding rituximab to first-line chemotherapy was associated with higher adjusted incremental total cost ($18,695; 95% Confidence Interval (CI) $9,302–$28,643) and longer adjusted cumulative survival (0.18 years; 95% CI 0.10–0.27) over four years of followup. The expected cost-effectiveness was $102,142 (95% CI $34,531–296,337) per life-year gained. In routine clinical practice, adding rituximab to first-line chemotherapy for elderly patients with FL results in higher direct medical costs to Medicare and longer cumulative survival after four years.

PurposeThe optimal management of stage I follicular lymphoma, according to consensus guidelines, is based on uncontrolled experiences of select institutions. Diverse treatment approaches are used despite guidelines that recommend radiation therapy (XRT).Patients and MethodsWe analyzed outcomes of patients with stage I follicular lymphoma enrolled onto the National LymphoCare database.ResultsOf 471 patients with stage I follicular lymphoma, 206 patients underwent rigorous staging as defined by both a bone marrow aspirate and biopsy and an imaging study (a computed tomography [CT] scan of the whole body, a positron emission tomography [PET]/CT scan, or both). Rigorously staged patients had superior progression-free survival (PFS) compared with nonrigorously staged patients (hazard ratio [HR], 0.63). Treatments given to rigorously staged patients were rituximab/chemotherapy (R-chemo; 28%), XRT (27%), observation (17%), systemic therapy + XRT (13%), rituximab monotherapy (12%), and other (3%). With a median follow-up of 57 months for PFS, there were 44 progression events (in 21% of patients) for rigorously staged patients. For these patients, PFS was significantly improved with either R-chemo or systemic therapy + XRT compared with patients receiving XRT alone after adjustment for histology, LDH, and the presence of B symptoms. There were no differences in overall survival.ConclusionIn this largest, prospectively enrolled group of patients with stage I follicular lymphoma, variable treatment approaches resulted in similar excellent outcomes, which challenges the paradigm that XRT should be standard for this presentation.

Abstract Background: Estrogen receptors are over-expressed in around 70% of breast cancer cases. The genetic changes that occur during aromatase inhibitor (AI) treatment are not well understood and may differ depending upon the patient's response phenotype. Methods: We performed whole genome sequencing (WGS) of matched blood, pre-treatment, and post-treatment biopsy samples from 22 estrogen receptor positive breast cancer patients treated with neoadjuvant aromatase inhibitors. For 5 cases, we performed the whole genome sequencing (WGS) on patients’ matched normal, two pre AI-treatment, and two post AI-treatment DNA isolates from biopsy samples. We validated all putative coding and non-coding somatic mutations using deep sequencing. By comparing the validated somatic mutations from pre- and post- AI treatment biopsy samples, we were able to determine the alterations in the tumor genomes. In every case we defined the clonal architecture of each pair of pre-treatment and post-treatment biopsy samples by comparing the variant allele frequencies from thousands of validated somatic mutations. Results: Comparisons of the two pre AI-treatment biopsy samples from the same patient indicates that the variant allele frequencies of mutations showed high concordances in all 5 cases, 0.74 to 0.95 range of correlation coefficient. Only a small percentage of somatic mutations were detected in one pre-treatment sample and not the other (4.65% overall). In comparing the somatic variations between pre-treatment and matched post-treatment biopsy samples in 22 cases, we found that patients with good clinical response to AI treatment retained known driver mutations only in their pre-treatment tumors. Conversely, those patients with poor clinical response presented new driver mutations in their post-treatment samples. Furthermore, the variant allele frequency for most mutated genes decreased in post AI treatment samples for patients with good AI treatment response; on the contrary, the variant allele frequency increased for patients with poor clinical response. Conclusions: From WGS of matched normal, pre-treatment, and post-treatment biopsy samples, we identified new driver genes mutated in patients with poor clinical response, while patients with good clinical response had lost mutated driver genes in their post-treatment biopsy samples. The genetic landscape revealed by WGS of pre-treatment and post-treatment biopsy samples reveals mutational repertoires are remodeled by AI therapy. This finding suggests deep sequencing of AI treated samples will be necessary to reveal the complete complement of mutations present in a patient's tumor. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-423. doi:1538-7445.AM2012-LB-423

Abstract Lung cancer in never-smokers is increasingly recognized as distinct from that in ever-smokers owing to substantial differences in etiology, clinical characteristics, and prognosis. Therefore, we aimed to identify prognostic markers specific for lung cancer in never-smokers in a two-stage study. First, 11,930 single-nucleotide polymorphisms (SNPs) in 904 inflammation-related genes were genotyped, and their associations with overall survival in 411 never-smokers with lung cancer at The University of Texas MD Anderson Cancer Center were analyzed. Next, fast-track validation of the top 37 SNPs in 311 never-smokers with lung cancer at Mayo Clinic was performed. Three SNPs (interleukin 17 receptor A:rs879576, bone morphogenetic protein 8A:rs698141, and spleen tyrosine kinase:rs290229) were validated (p<0.05), and two more SNPs (CD74:rs1056400 and CD38:rs10805347) were borderline significant (p=0.08) in the Mayo Clinic population. In combined analysis of the MD Anderson and Mayo Clinic patients, IL17RA:rs879576 resulted in a 40% reduction in the risk of death (p=4.1 × 10−5 [p=0.61, heterogeneity test]). We successfully validated a survival tree created in MD Anderson population based on gene-gene interactions in the Mayo Clinic population. This survival tree stratified patients into subsets with significantly different risks of death: patients at MD Anderson with the rs1056400_GG/rs698141_GA+AA genotype had a 2.32-fold higher risk of death (p=1.72 × 10−5) and 9-month shorter median survival time (MST) (p=4.5 × 10−4, log-rank test) than did those with the rs1056400_GG/rs698141_GG or rs1056400_GA+AA genotype in the discovery phase. Also, the patients at Mayo Clinic with the former genotype had an approximately twofold higher risk of death (p=0.02) and a strikingly shorter (by 26 months) MST (p=0.029, log-rank test) than did those with the latter genotype in the validation phase. We evaluated these five SNPs in 996 ever-smokers and found no significant associations. To our knowledge, this is the first study to systematically evaluate the associations of genetic variations in major inflammation-related genes with outcome of lung cancer in never-smokers. It provides strong evidence that inflammation-related genetic variations can affect clinical outcomes in these patients, which may lead to significant biological insight into these outcomes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2929. doi:1538-7445.AM2012-2929