Aspergillus species and Candida albicans). Deletions and missense, frameshift, or nonsense mutations in the gp91phox gene , located in the Xp21.1 region of the X chromosome, are associated with the most common form of CGD. When larger X-chromosomal deletions occur, including the XK gene deletion, a so-called "Contiguous Gene Deletion Syndrome" may result. The contiguous gene deletion syndrome is known to associate the Kell phenotype/McLeod syndrome with diseases such as X-linked chronic granulomatous disease, Duchenne muscular dystrophy, and X-linked retinitis pigmentosa. These patients are often complicated and management requires special attention to the various facets of the syndrome.Chronic Granulomatous Disease (CGD), a disorder of the NADPH oxidase system, results in phagocyte functional defects and subsequent infections with bacterial and fungal pathogens (such as  Staphylococcus aureus, Pseudomonas species, Nocardia species, fungi such as Aspergillus species, and Candida albicans. Significant morbidity and mortality may result.Primary immune deficiencies can involve defects in phagocyte function, resulting in Chronic granulomatous disease (CGD) ,2. CGD iThe genetic defect in CGD can be transmitted in either an X-linked or autosomal recessive manner ,5-7. Genphox gene, which is also referred to as the cytochrome b-245 beta polypeptide (CYBB) gene. Autosomal recessive CGD is seen in the remaining 35% of cases and arises due to mutations of the other components of the NADPH oxidase system [phox , p67phox, and p47phox . Of these, the dominant mutation observed is in the p22phox gene which accounts for almost 25% of the autosomal recessive cases. The associated phenotypes are also referred to as the A22/A47/A67 CGD. The phenotype of the gp91phox gene mutation is referred to as X-CGD. Mutations of other nearby genes, p40phox and Rac, have yet to be associated with any CGD phenotype [X-linked CGD is responsible for the majority (> 60%) of the CGD cases seen in the United States ,20. The e system ,2,5-7. TThe CYBB gene spans a 30 kb region in the Xp21.1 region of the X chromosome Figure . DeletioThe Kell blood group system was first identified by Coombs in 1946 when ABO and Rhesus incompatibility were excluded in a mother, Mrs. Kelleher, who had delivered a baby with hemolytic anemia. It is now considered the third most important blood group system based on immunological potency. The antigens of the Kell system are numerous and complex ,21-25. TThe Kell antigens, which are encoded for by the KEL gene, are carried by the transmembrane Kell glycoprotein (XK) Figure . The KEL0). Individuals with this phenotype produce anti-Ku antibodies that target RBCs expressing Kell antigens, but are otherwise healthy. Anti-Ku antibodies may result in the development of moderate to severe transfusion reactions following transfusion from a donor who is Kell+. For this reason, patients with the K0 phenotype should only be transfused with K0 blood products. Anti-Ku antibodies are also involved in fetomaternal immunization. Pregnant females with the K0 phenotype produce anti-Ku antibodies which target Kell antigens located on the surface of fetal RBCs. These antibodies are responsible for the third most common cause of hemolytic anemia in the newborn. The McLeod phenotype is seen with a severe reduction in Kell antigens; this can be associated with CGD [Although there have been 25 Kell antigens identified, the "k" antigen is the most common. The phenotype K-k+ is seen in a majority of Caucasians and African Americans, while a smaller number (9%) of Caucasians may be K+k+. When the Kell antigens are absent on red blood cells, this is referred to as the rare K null phenotype (Kwith CGD -25.th decade or later) of neuropsychological or cardiovascular impairment in patients with CGD.The McLeod syndrome is characterized by an absence of the Kx antigen on red blood cells. This is associated with weak expression of Kell antigens. Kell antigens are covalently bound to the RBC transmembrane XK protein. When XK is absent on RBC membranes, McLeod syndrome develops. In this syndrome, the Kell antigens are weakly expressed which leads to the appearance of abnormally shaped RBCs (referred to as acanthocytes) . Charactnd and 6th decades of life. Besides Huntington's chorea-like disease and cardiomyopathy, patients develop muscle weakness and atrophy, psychiatric disease, and cognitive impairment [As reviewed by Jung et al., this disorder may be discovered accidentally by routine screening of apparently healthy blood donors . Affectepairment ,17,29-34pairment . It is tDMD is an X-linked progressive myopathy that can occasionally complicate a contiguous gene deletion syndrome involving X-linked CGD ,34. In tRPGR gene, is seen in the Contiguous gene deletion syndrome. Clinically, there is progressive loss of visual acuity and night blindness followed by a rapid decline in vision and blindness by the 4th decade.This is a condition that leads to progressive visual loss due to loss of the photoreceptors. There are several reports of Retinitis pigmentosa complicating CGD and the Contiguous gene deletion syndrome ,34,36-38CGD is a chronic disease caused by a mutation in a gene encoding essential components of NADPH oxidase function. As a result, increased susceptibility for infections occurs. The more common form of CGD involves the gene regulating NADPH function that is located on the X-chromosome. A deletion that results in X-linked CGD can also involve contiguous genes. This results in the "contiguous X-chromosome gene deletion syndrome" with manifestations of the McLeod syndrome, Duchenne muscular dystrophy and X-linked retinitis pigmentosa that further complicate disease severity and management.CGD: chronic granulomatous disease; CGS: contiguous gene syndrome; RBC: red blood cell; CYBB: cytochrome b-245 beta polypeptide.The authors declare that they have no competing interests.CW-organized and assisted in writing manuscript; JL-assisted with manuscript review; ES-assisted in writing manuscript; GJ-assisted in writing manuscript; NM-assisted with manuscript review and corrections; NH-assisted with figure and literature review; MD-assisted with generating figure; GK-conceived of the manuscript, generated all figures and developed the format. All authors have read and approved the final manuscript.


Hypoplastic Left Heart Syndrome (HLHS) is a congenital defect characterized by underdevelopment of the left ventricle and pathological compensation of the right ventricle. If untreated, HLHS is invariably lethal due to the extensive increase in right ventricular workload and eventual failure. Despite the clinical significance, little is known about the molecular pathobiological state of HLHS. Splicing of mRNA transcripts is an important regulatory mechanism of gene expression. Tissue specific alterations of this process have been associated with several cardiac diseases, however, transcriptional signature profiles related to HLHS are unknown. In this study, we performed genome-wide exon array analysis to determine differentially expressed genes and alternatively spliced transcripts in the right ventricle (RV) of six neonates with HLHS, compared to the RV and left ventricle (LV) from non-diseased control subjects. In HLHS, over 180 genes were differentially expressed and 1800 were differentially spliced, leading to changes in a variety of biological processes involving cell metabolism, cytoskeleton, and cell adherence. Additional hierarchical clustering analysis revealed that differential gene expression and mRNA splicing patterns identified in HLHS are unique compared to non-diseased tissue. Our findings suggest that gene expression and mRNA splicing are broadly dysregulated in the RV myocardium of HLHS neonates. In addition, our analysis identified transcriptome profiles representative of molecular biomarkers of HLHS that could be used in the future for diagnostic and prognostic stratification to improve patient outcome. In Hypoplastic Left Heart Syndrome (HLHS), the right ventricle (RV) is exposed to pressure overload, volume overload, and hypoxia.Alterations in mRNA expression and splicing have previously been reported in a wide range of adult cardiac disease states,The objective of this study was to characterize mRNA expression and splicing patterns in the RV myocardium of HLHS newborns by utilizing genome-wide exon-level interrogation, hypothesizing that mRNA expression and splicing profiles are dysregulated in the HLHS myocardium as compared to control LV and RV myocardium. As RV failure is the strongest predictor of long-term outcome in HLHS, our study focused on defining the gene expression and splicing patterns in the HLHS right ventricular myocardium to provide insights into the molecular mechanisms associated with RV adaptation or remodeling. In addition, as previous work by our group has shown that TGF-β-associated gene expression profiles in the HLHS-RV share greater molecular similarities with Control-LV than Control-RV,-18 Autopsy specimens were collected by the same operator and absence of heart valve pathology was confirmed during post-mortem examination. Consistent with HLHS tissue harvesting, full-thickness RV tissue was obtained from the same area of the RV free wall in controls, whereas LV tissue was obtained from the mid-portion of the free wall. In each experimental group, approximately 50 mg of ventricular tissue were removed, snap frozen in liquid nitrogen, and stored at −80°C until RNA extraction.This study was approved by the Institutional Review Board at the University of Miami (Protocol #20101106). For this study, tissue samples were collected from three experimental groups as follows: 1) six RV samples from neonates with HLHS (HLHS-RV), 2) five RV samples from control neonates (control-RV), and 3) five LV samples from the same control neonates (control-LV). As previously reported,RNA was extracted using TRIzol reagent (Invitrogen) or Qiagen RNeasy Mini Kit according to the manufacturer's instructions. In all samples, RNA integrity and purity were determined with the Agilent 2100 Bioanalyzer . For microarray analysis, RNA samples were amplified and labeled using NuGEN Ovation Pico WTA system, WT-Ovation Exon module and Encore Biotin Module . Briefly 20 to 50ng of total RNA were subjected to the synthesis of first-strand cDNA using a unique DNA/RNA chimeric primer mix and reverse transcriptase. DNA-RNA heteroduplex double-strand cDNA was generated and subjected to SPIA amplification, using an SPIA DNA/RNA chimeric primer, DNA polymerase and RNase H in a homogeneous isothermal assay. The resulting cDNA was used to generate sense transcript cDNA suitable for fragmentation and labeling as target for Affymetrix Human Exon 1.0 ST arrays.oC in the Affymetrix Hybridization Oven 645 according to the manufacturer's instructions. After hybridization, microarrays were washed, stained using the Affymetrix Fluidics Station 450, and scanned with the Affymetrix Scanner 3000 7G.Microarrays (Affymetrix Human Exon 1.0 ST Arrays)http://eaa.mpi-bn.mpg.de/) and R respectively for quality control, and then processed by Affymetrix power tools (APT) for background correction, normalization, and summarizations with the Robust Multiple Average (RMA) algorithm to generate exon- and gene-level intensity estimates. The analysis was restricted to 287,329 exon-level and 22,011 gene-level core probe sets by selecting the core.ps and core.mps file options during exon- and gene-level processing with APT. The number of exon-level probe sets for consideration was further reduced by removing known cross-hybridizing exon-level probe-sets, per annotation file “HuEx-1_0-st-v2.na31.hg19.probeset.csv”.Images were analyzed with the Affymetrix Command Console Software. The resulting CEL files were loaded into Exon Array Analyzer  p value was <0.05 in <50% of the samples of at least one of the three treatment groups. In the second filtration step, a transcript cluster was marked as detected if >50% of exon-level probe sets comprising the cluster were detected per filtration step 1.2 (exon-level probe set intensity/gene-level probe set intensity). BioConductor LIMMA package was used for differential analysis. One-way ANOVA of splicing indexes and gene-level probe intensities was performed to identify exon-level and gene-level probe sets (i.e. transcript clusters) showing significant changes in intensity among the three treatment groups. T tests were additionally used for comparisons amongst two groups: HLHS-RV vs. Control-RV and HLHS-RV vs. Control-LV. The false discovery rate (FDR) for each P value was calculated by the method of Benjamini and Hochberg.The splicing index for each exon was calculated as: logGenes corresponding to differentially expressed transcript clusters or exon probe sets with an altered splice index were selected for representation in Venn diagrams and further pathway analysis, providing threshold criteria were met  difference of >1.5-fold). WebGestalt Software (Vanderbilt University)2-transformed data were pre-processed by median centering of the data for each probe set, and then hierarchically clustered using centered correlation as the similarity metric and average linkage as clustering method.Criteria for selection of differentially expressed transcript clusters or exon probe sets with an altered splice index for display in hierarchical clustering was the same as for the pathway analysis, other than a 2-fold change threshold in gene-level probe set intensity or a 5-fold change in splicing-index for exon-level probe sets were applied. Data for the detectable probes were clustered using Cluster 3.0 software.http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=hfapraoacwqgwhg&acc=GSE23959.Principal component analysis was conducted using Partek to visualize the overall pattern of gene expression. All data is MIAME-compliant (Minimum Information About a Microarray Experiment) and all CEL files for this microarray study are available through The Gene Expression Omnibus at: 18s, GAPDH) and 94 random genes that significantly changed in the microarray analysis as described.21 Cycle counts for each target gene were normalized to 18s expression, and significant differences in gene expression were reported as a fold change compared to each experimental group.21To validate differential fold changes in gene expression between the comparison groups from the microarray analysis, cDNA was generated from 400 ng tRNA from human samples using the High Capacity Reverse Transcriptase kit (Applied Biosystems). Then, 10 µL cDNA were subjected to quantitative real-time PCR using a custom-designed Taqman Low Density Array (Applied Biosystems) containing two endogenous controls  was performed using total RNA isolated from the RV myocardium of neonates with HLHS (n = 6) (HLHS-RV), and compared to RNA collected from control-RV (n = 5), and control-LV (n = 5) samples. For each RNA sample collected, the analysis was performed using the Agilent Bio-analyzer 2100 to confirm consistently high levels of RNA integrity and purity across the sample groups. The clinical and echocardiographic data of the six HLHS neonates included in this study are shown in In this study, RNA was hybridized to Affymetrix arrays containing approximately 40 probes per gene and 4 probes per exon, therefore allowing two complementary levels of analysis in the same samples at the levels of gene expression and alternative splicing, respectively. One-way ANOVA analysis was performed to compare ‘core’ gene  expression and alternative splicing profiles in HLHS-RV tissue vs. Control-LV, and Control-RV samples. Significant changes were considered with fold changes in gene expression and splicing index >1.5 and a false discovery rate (FDR) of <0.05. Using these parameters to compare HLHS-RV to control samples, a total of 183 genes were differentially expressed: 153 genes in HLHS-RV vs. Control-LV, 96 genes when compared to Control-RV, with 66 genes overlapping between the two comparison groups . Tables GTF2I, LANCL2, PLOD2, SOS2, USP2 and ZFP3) are shown in To confirm observations from the microarray data, a total of 94 randomly selected genes that passed the threshold criteria were validated by quantitative real-time PCR in n = 4 samples from each subject group . Of the 94 genes, more than 86% showed consistent differential changes in gene expression in HLHS-RV samples when compared to the respective control groups. Examples of 6 validated genes  plot . This anTo further examine whether HLHS-RV gene expression and alternative splicing profiles segregated from control samples, hierarchical clustering analysis was performed. To determine the biological processes altered in the early stage HLHS-RV pathogenesis, KEGG pathway analysis was performed. To determine alterations in the abundance of individual exons of alternatively spliced genes in HLHS-RV, expression profiling was performed. Recent studies have partly unveiled the chromosomal loci associated with hereditary HLHS,Signature profiles of gene expression have been used as tools for diagnostic and prognostic purposes in human cardiomyopathies.,,Prp 2, 16–18, 53), consistent with the overrepresentation of the ‘spliceosome’ and consistent with splicing events. In addition, genes involved with cell-cell communication , cytoskeleton , and calcium movement  were largely underexpressed in HLHS-RV. These latter changes are consistent with compensatory remodeling in the RV of HLHS patients to support pathophysiological changes in hemodynamic load as a result of an underdeveloped LV. Although informative, we cannot determine if the observed changes in gene expression and mRNA splicing are causative of HLHS or the result of adaptive or maladaptive myocardial changes in the RV myocardium of HLHS subjects. Nonetheless, this analysis provides insights into the biological processes that are altered in the HLHS-RV as a result of changes in transcriptome profiles.In addition to altered whole-gene expression patterns, altered splicing patterns resulting in differential exon abundance in HLHS tissue are also consistent with other studies of adult cardiac disease states.SLC8A1, CACNB2, RYR1) and energy metabolism  genes, as well as structural proteins , detectable in myocardial samples obtained from HLHS patients during surgical intervention. In addition to tissue-specific biomarkers, levels of secreted factors  and cell surface markers (PROM1) have previously shown to be measurable in serum samples and serve as biomarkers for other pathological states.In this study we have identified a number of differentially expressed and differentially spliced transcripts that have the potential to serve as biomarkers of HLHS disease state. These include differential expression and splicing of calcium transporter Click here for additional data file.


To investigate the prognostic significance of disseminated tumor cells (DTCs) in bone marrow (BM) from non-metastatic breast cancer patients before and after surgery.Patients with non-metastatic breast cancer were consecutively recruited to this project during the years 1998–2000. Real-time RT-PCR quantification of a DTC multimarker panel consisting of cytokeratin 19, mammaglobin A and TWIST1 mRNA was performed in BM samples obtained from 154 patients three weeks (BM2) and/or six months after surgery (BM3). The results were compared to previously published data from pre-operative BM analyses for the same patients.p < 0.001) and breast-cancer specific survival . Furthermore, the prognostic value of DTCs in BM was similar for pre- and post surgery samples. However, patients with DTCs both before and after surgery (BM1 and BM2/3) had a particularly poor prognosis .DTCs were identified in post-operative BM samples (BM2 and/or BM3) from 23 (15%) of the 154 patients investigated. During a median follow-up of 98 months, 10 (44%) of these patients experienced systemic relapse as compared to 16 (12%) of 131 DTC-negative patients. Kaplan-Meier estimates of systemic recurrence-free- and breast-cancer specific survival demonstrated significantly shorter survival for patients with persistent DTCs in BM after surgery (p≤0.001). By multivariate Cox regression analyses, persistent DTCs after surgery was an independent predictor of both systemic recurrence-free- (HR = 5.4, Detection of persistent DTCs in BM samples obtained after surgery identified non-metastatic breast cancer patients at high risk for systemic relapse, and with reduced breast-cancer specific survival. Furthermore, patients with positive DTC status both before and after surgery had a particularly poor prognosis. There is considerable evidence that detection of disseminated tumor cells (DTCs) in pre-operative bone marrow (BM) samples from non-metastatic breast cancer patients identifies a patient population at high risk for disease recurrence -5. DTCs et al. (2009), with samples collected before and after adjuvant chemotherapy )We have previously demonstrated by a MM quantitative RT-PCR panel that detection of DTCs in pre-operative BM samples BM1) predicts clinical outcome in non-metastatic breast cancer patients . In orde predictsp = 0.12) towards a higher frequency of N0 patients with lower differentiation grade in the BM2 sampling group.Since not all of the patients who provided a BM aspiration prior to surgery agreed to provide BM aspirations three weeks (BM2) and/or six months after surgery (BM3), we tested by Fisher’s exact test if there were any biases between the different sample groups included in this study. No significant differences were found between the 45 patients only providing BM2, and the 99 patients who provided both BM2 and BM3 aspirations. However, there was a trend  and recurrence-free survival (p < 0.001) was also demonstrated (data not shown). Moreover, when we stratified the Kaplan-Meier analyses of systemic recurrence-free survival according to LN status, the post-operative DTC status was demonstrated to be a strong prognostic factor in both the LN-negative (p = 0.007) and the LN-positive patients .During a median follow-up of 98 months, 10 out of the 23 (44%) patients with persistent DTCs detected in at least one of the two post-operative BM samples experienced systemic relapse , three weeks BM2) and six months (BM3) after primary surgery by three separate multivariate Cox regressions, also including other prognostic factors, and found only small differences in the hazard ratios between the three time points Table . However and six p = 0.001 for systemic-recurrence-free survival) [et al. (2009), in which the estimated prognostic effect of DTCs in BM samples collected shortly after adjuvant chemotherapy was similar to the effect in BM samples collected post-operatively, prior to chemotherapy [We have previously demonstrated that the presence of DTCs, in terms of MM mRNA levels above the established cut-off values, in BM samples obtained prior to breast cancer surgery provide significant prognostic information  . In the otherapy . Similar [et al. 009, in wotherapy .et al. (2004), although it was not as striking as in our study. In their study, the estimated 5-year distant disease-free survival was <70% for the patients with DTC-positive BM both at diagnosis and after three years, as compared to ~80% for the whole group of patients who were DTC positive only in the second BM sample [The results in the present study do, however, suggest that a positive pre-operative DTC status, if confirmed in a second BM sample collected three weeks or six months post-operatively (double positive), predicts a particularly poor prognosis. The estimated 8-year systemic recurrence-free survival in this group of patients was in fact <20% Figure A. A simiM sample . HoweverIt would be interesting to investigate whether DTC detection after adjuvant therapy could be a surrogate marker for evaluation of treatment efficiency. However, due to small patient numbers in the subgroups receiving adjuvant treatment it was not possible to conclude on the potential for monitoring or prediction of adjuvant treatment efficiency in this study. This important aspect should be addressed in new studies.Discrepancies between the methods used to detect DTCs could make it difficult to compare studies using different methodologies. Immunocytochemistry has the advantages of being able to characterize cell size, cell shape and atypical enlargement of nucleus which may occur in malignant cells. However, due to the absence of tumor-specific targets, monoclonal antibodies against various epithelium-specific antigens, like the cytokeratins, are mostly used. In comparison, molecular methods are highly sensitive and may detect DTCs based on their expression of tumor-specific markers. One disadvantage is nevertheless that the cells cannot be morphologically characterized by the use of molecular methods. However, molecular profiling of breast cancer cells may be used to characterize and classify the tumor cells according to their protein, DNA or mRNA pattern., our results seem to correspond with Wiedswang et al. (2004) also showing that 15% of the non-metastatic breast cancer patients had detectable DTCs in BM at a median 66 months from diagnosis [et al. (2005) detected DTCs in 13% of the patients after surgery [et al. (2009) using real-time RT-PCR for detection of CK19 mRNA-positive DTCs is, however, in contrast to these results. In their study, 58% of the non-metastatic breast cancer patients had BM DTCs detected after surgery, prior to chemotherapy, and 51% after chemotherapy [In the present study we demonstrate that 15% of the patients with non-metastatic breast cancer have DTCs detected in BM after primary surgery Table . Althoug surgery . An Euro surgery . The DTCotherapy . The lowotherapy .et al. (2009) regarding the high fraction of patients with CK19-positive DTCs in BM after surgery in their study [We observed that the contribution of CK19 to DTC detection, relative to hMAM and TWIST1, was lower after surgery than prior to surgery Table . This obir study . Thus, tDespite the establishment of the prognostic and predictive significance of BM DTCs ,16,19, dDetection of DTCs by our MM mRNA panel in BM collected after surgery identified non-metastatic breast cancer patients at high risk for systemic relapse, and with reduced breast-cancer specific survival. Furthermore, patients with positive DTC status both before and after surgery are recognized as patients with an extremely poor prognosis. Thus, a strategy involving a BM aspirate during general anesthesia, prior to surgery, with a repeated, post-operative aspiration performed only among patients who were DTC positive in the first sample, should be feasible and having significant clinical relevance. Moreover, although we may not conclude on the potential of DTC status for monitoring the efficiency of adjuvant treatment, the strong prognostic effect of DTCs observed after surgery suggests that such monitoring may be of importance. Future studies are required to determine whether the patients with inferior outcome predicted by DTC detection, especially those with DTCs detected both before and after surgery, may benefit from intensified or secondary adjuvant therapy.The authors declare that they have no competing interests.KT carried out all the qRT-PCR analyses, performed the statistical analyses and drafted the manuscript. SO did all the RNA purification, and participated in manuscript preparation. RH participated in sample collection, study design and manuscript preparation. Statistician JTK participated in the statistical evaluation, and preparation of the manuscript. BG participated in sample collection, and manuscript preparation. JMR gave scientific advice, contributed to data interpretation and manuscript preparation in addition to correcting the English grammar. RS is the group leader and contributed to result interpretation, supervision and manuscript preparation. ON participated in the study design, coordinated the study, gave statistical advice and contributed to the manuscript preparation. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/12/190/prepub


In patients with schizophrenia, early non-response to oral antipsychotic therapy robustly predicts subsequent non-response to continued treatment with the same medication. This study assessed whether early response predicted later response when using a long-acting injection (LAI) antipsychotic.0-6) Total score. Subsequent response was defined as ≥40% baseline-to-endpoint improvement in PANSS0-6 Total score. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and predictive accuracy were calculated. Clinical and functional outcomes were compared between Early Responders and Early Non-responders.Data were taken from an 8-week, randomized, double-blind, placebo-controlled study of olanzapine LAI in acutely ill patients with schizophrenia (n = 233). Early response was defined as ≥30% improvement from baseline to Week 4 in Positive and Negative Syndrome Scale . Among Early Non-responders, 20% demonstrated response by Week 8. Patients who lacked early improvement (at Week 4) in Negative Symptoms and Disorganized Thoughts were more likely to continue being non-responders at Week 8.Early response/non-response to olanzapine LAI predicted later response/non-response with high sensitivity (85%), specificity (72%), PPV (78%), NPV (80%), and overall accuracy (79%). Compared to Early Non-responders, Early Responders had significantly greater improvement in PANSSAmong acutely ill patients with schizophrenia, early response predicted subsequent response to olanzapine LAI. Early Responders experienced significantly better clinical and functional outcomes than Early Non-responders. Findings are consistent with previous research on oral antipsychotics.http://clinicaltrials.gov/ct2/show/NCT00088478?term=olanzapine+depot&rank=3F1D-MC-HGJZ: Comparison of Intramuscular Olanzapine Depot With Placebo in the Treatment of Patients With Schizophrenia NCT00088478Registry identifier -  The time-course of response to antipsychotic therapy has been extensively evaluated, and the original belief that it took between 6 and 8 weeks to determine a therapy's effectiveness in patients with schizophrenia has largely been abandoned . In manyRecently, there has been much interest in early response or non-response to treatment as a predictor of subsequent response to the same treatment. Failure to respond in the first 1 to 2 weeks of therapy has been shown to robustly predict later failure to respond to continued use of the same medication, a finding seen both in patients with chronic schizophrenia -8. and iThe trajectory of symptomatic improvement for patients who respond early to oral antipsychotic medication clearly differs from that of patients who do not show early response. The early responder groups have had higher baseline illness severity, more rapid symptom improvement, and consistently greater magnitude of improvement over time ,7. InvesWhether patients who do or do not respond early to injectable antipsychotics differ in their functional outcomes or sense of health status also is not known. There is evidence based on analyses of response to oral antipsychotics to suggest that differences in functional outcome may exist. In a post hoc analysis of a 1-year, randomized, open-label study of oral antipsychotics, patients who demonstrated early response had greater improvement from baseline to Week 8 in measures of mental, physical, and functional health than those who did not respond early . SimilarIt is not known whether the predictive power of early response to oral antipsychotic therapy extends to long-acting injection (LAI) antipsychotics. Olanzapine LAI has been shown to have an early onset of action, with clinical improvement detectable as early as the first week of treatment. Although olanzapine LAI provides therapeutic drug levels following the first injection, drug levels continue to accumulate, reaching steady state olanzapine plasma concentrations approximately 3 months after initiation of therapy . Given tThe primary objective of this analysis is to assess whether response to olanzapine LAI at Week 4 of treatment predicts response/non-response at Week 8 of treatment in acutely ill patients with schizophrenia. Secondary objectives include identifying baseline characteristics that might help differentiate Early Responders from non-responders, searching for differences in functional outcome between Early Responders and Early Non-responders, and identifying factors that predict later response in those patients who do not respond early.NCT00088478; http://clinicaltrials.gov/ct2/show/NCT00088478?term=olanzapine+depot&rank=3).This was a post hoc analysis of data from an 8-week, randomized, double-blind trial comparing multiple dosing regimens of olanzapine LAI with placebo for treatment of acutely ill patients with schizophrenia . PatientAfter a 2- to 7-day screening and washout period, patients were randomly assigned (1:1:1:1) to receive olanzapine LAI in doses of 210 mg/2 weeks, 300 mg/2 weeks, 405 mg/4 weeks, or placebo. Patients entered as inpatients or outpatients, but were hospitalized during the wash-out period and for the first 2 weeks of treatment. If a patient had previously received depot antipsychotics, the interval since the last dose had to be 3 weeks or 1 injection interval, whichever was longer. Concomitant use of central nervous system medication was prohibited, except for limited use of select benzodiazepines/sedatives as needed for sleep.The primary outcome was mean baseline-to-endpoint change (last observation carried forward) in PANSS Total score after 8 weeks of treatment. The PANSS is a 30-item scale with each item scored between 1 (no symptoms) and 7 (severe symptoms), from which are derived a Total score, and Positive, Negative, and General Psychopathology subscores. The PANSS was administered at baseline, Day 3, Day 7, and weekly thereafter. Patients were assessed with the Short Form-36 Health Survey (SF-36) . and the0-6 Total score at Week 4, and "later response" was defined as a ≥40% improvement over the baseline PANSS0-6 Total score at Week 8. Using these thresholds, patients were identified as "Early Responders" or "Early Non-responders" and "Late Responders" or "Late Non-responders." As suggested by Leucht et al. [1-7 so that the range of scores was 0 to 6 rather than 1 to 7, such that the minimum score  for the PANSS0-6 was 0 rather than 30. Rescaling of the PANSS1-7 prevented an underestimate of percentage improvement, since a 100% reduction in PANSS score is not possible using the other scaling convention ["Early response" was defined as a ≥30% improvement over the baseline PANSSt et al. . we rescnvention .This analysis included the 233 patients who received olanzapine LAI and who had a PANSS Total score at Week 4 and at least 1 PANSS Total score after Week 4. Conditional probabilities of early response (Week 4) predicting later response (Week 8) were calculated and included sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and total accuracy. To assess for differences between Early Responder and Early Non-responder groups, baseline characteristics for each group were compared using Fisher's exact test for categorical variables and t-test for continuous variables.Least square (LS) mean change from baseline in PANSS Total score was compared between responder groups at each time point using a mixed model repeated measures method with baseline PANSS Total score, investigator, responder status, week, and responder status-by-week interaction terms.Baseline-to-endpoint change in the Davis factor subscales of the PANSS were compared between Early Responder and Early Non-responder groups using an analysis of covariance model that included baseline score, investigator, and responder status. In 2001, Davis et al. . used faFor all analyses, results were considered significant at the p < .05 level and all statistical analyses were conducted using SAS .The original study enrolled 404 patients, 306 of whom were treated with olanzapine LAI. Of the 306 patients, 233 (76%) met eligibility criteria for this analysis. Of these patients, 137 (58.8%) were identified as Early Responders and 96 (41.2%) were identified as Early Non-responders. The baseline characteristics of the Early Responder and Early Non-responder groups are shown in Table Response at Week 4 predicted response at Week 8 with a good degree of accuracy. Sensitivity was 84.9%, specificity was 72.0%, PPV was 78.1%, NPV was 80.2%, and total accuracy was 79.0% , Mental Health (p=.004), and Social Functioning (p=.002). On the QLS, Early Responders had significantly greater improvement than Early Non-responders for the Total score (p < .001) and all subscales .Of the 96 patients who did not meet criteria for response at Week 4, 19 patients (20%) met criteria for subsequent response. In the regression model, lack of improvement in the Negative Symptom and the Disorganized Thoughts factors predicted non-response at endpoint for patients who had not responded by Week 4. Specifically, lack of at least a 3-point drop from baseline in both of these factor scores at Week 4 predicted continued non-response with a 48% PPV, 91% NPV, 68% sensitivity, and 82% specificity  was found to predict subsequent response (Week 8) with high degrees of sensitivity, specificity, PPV, and NPV, and an overall accuracy level of 79%. The group of patients who met criteria for early response had a trajectory of symptom recovery that was distinct from that of the group who did not meet response criteria. Compared to Early Non-responders, Early Responders had a higher level of symptom severity at baseline as measured by PANSS Total score, and had a greater degree of improvement over baseline at every subsequent time point. By Week 8, improvement by Early Responders was more than double that of Early Non-responders (-37 points vs. -15 points).The total accuracy of predicting later response to olanzapine LAI based on early response exceeded that seen in studies of oral antipsychotics, including analyses of patients with chronic schizophrenia,. of patiA comparison of rates of study discontinuation between Early Responders and Early Non-responders was included in this analysis because this outcome is associated with increased rates of relapse and psychiatric hospitalization, decreased functional outcome and quality of life, and increased treatment costs ,18-22. MEarly Responders to olanzapine LAI differed significantly from Early Non-responders at baseline by having higher PANSS Total scores. In prior studies of oral antipsychotics for treatment of patients with chronic schizophrenia, Early Responders also had higher baseline PANSS Total scores than Early Non-responders,,7. thougEarly improvement in symptoms of schizophrenia in response to olanzapine LAI not only predicted later response in a total measure of symptoms of schizophrenia, but also predicted baseline-to-endpoint improvement across multiple symptom domains and other measures of quality of life, mental health, and social functioning. This study highlights potential benefits to patients, clinicians, families, and payers of early evaluation and identification of patients responding poorly to treatment. These findings echo those of Ascher-Svanum et al.,. who fouOf the patients who did not meet criteria for response at Week 4, 1 in 4 went on to meet the criteria for response at Week 8. A regression model to identify characteristics that distinguish Early Non-responders who do and do not respond at a subsequent time point found that lack of early improvement in 2 PANSS subscale scores - Negative Symptoms and Disorganized Thoughts - predicted continued non-response at endpoint. Specifically, lack of at least a 3-point drop in the Negative subscale score and lack of at least a 3-point drop in the Disorganized Thoughts subscale score at 4 weeks predicted continued non-response. Using this secondary predictive model as a confirming diagnostic test, lack of subsequent response could be predicted with near certainty (NPV = 91%). This secondary prediction model could potentially help in situations where clinicians need reassurance before proceeding with a change in treatment strategy.This analysis had several limitations that should be noted. First, it focused on a sample that consisted predominantly of inpatients who were acutely, markedly ill at baseline and had a history of multiple relapses. Results cannot be extrapolated to patients with less severe symptomology or who are earlier in their course of illness. This analysis used data from a trial that was 8 weeks in length. Further study is needed to assess this phenomenon over a longer treatment period. Also, the 30-item PANSS used to assess early response/non-response is a lengthy measure that is not used in usual clinical practice, thus potentially limiting the clinical applicability of our findings. However, we have recently identified 6 PANSS items that can be used to reliably assess response/non-response to oral antipsychotics with only a slight loss in predictive accuracy . WhetherIn the course of treatment of acutely ill patients with schizophrenia, early response to olanzapine LAI was found to predict later response with a high degree of accuracy, similar to that seen with oral antipsychotics. Although patient demographics were not helpful in distinguishing Early Responders from Early Non-responders, greater baseline symptom severity, particularly in the depressive and negative symptom domains, did help identify those patients more likely to respond early. Future analyses may want to further examine the predictive value of these factors, as they have utility in identifying response trajectories, as well . Nearly Drs. Ascher-Svanum, Zhao, Detke, Stauffer, Witte, and McDonnell, and Mr. Nyhuis, Lawson, and Montgomery are full-time employees of Eli Lilly and/or any of its subsidiaries, and minor stockholders of Eli Lilly and Company.All authors contributed to the development and content of the manuscript, and approved the final version, and qualify for authorship under the International Committee of Medial Journal Editor's Uniform Requirements for Manuscripts Submitted to Biomedical Journals (NEJM 1997(336):309-315 guidelines).The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/11/152/prepub


To describe changes in health-related quality of life (HRQoL) of postmenopausal women with osteoporosis treated with teriparatide for up to 18 months and followed-up for a further 18 months, and to assess the influence of recent prior and incident fractures.post-hoc analysis examined fracture impact on HRQoL in four subgroups classified based on recent prior fracture 12 months before baseline and incident clinical fractures during the study. Changes from baseline were analysed using a repeated measures model.The European Forsteo Observational Study (EFOS) is an observational, prospective, multinational study measuring HRQoL using the EQ-5D. The primary objective was to assess changes in HRQoL during 36 months in the whole study population. A secondary Of the 1581 patients, 48.4% had a recent prior fracture and 15.6% of these patients had an incident fracture during follow-up. 10.9% of the 816 patients with no recent prior fracture had an incident fracture. Baseline mean EQ-VAS scores were similar across the subgroups. In the total study cohort (n = 1581), HRQoL (EQ-VAS and EQ-5D index scores) improved significantly from baseline to 18 months and this improvement was maintained over the 18-month post-teriparatide period. Improvements were seen across all five EQ-5D domains during teriparatide treatment that were maintained after teriparatide was discontinued. Subjects with incident clinical fractures had significantly less improvement in EQ-VAS than those without incident fractures. Recent prior fracture did not influence the change in EQ-VAS during treatment.EFOS is the first longitudinal study in women with severe postmenopausal osteoporosis in the real world setting to show a substantial improvement in HRQoL during teriparatide treatment that was sustained during subsequent treatment with other medications. The increase in HRQoL was lower in the subgroups with incident fracture but was not influenced by recent prior fracture. The results should be interpreted in the context of the design of an observational study. The quality of life of postmenopausal women with osteoporosis is adversely affected if they have bone fractures and pain -6. HealtOsteoporosis treatment aims to prevent fractures and, in turn, to reduce morbidity and mortality. The efficacy of osteoporosis medications in reducing the risk of fragility fractures in postmenopausal women with osteoporosis has been demonstrated in randomised controlled trials (RCTs), but there is only limited data that they are capable of improving patient quality of life -20 or reResults from the ICARO observational study showed that osteoporotic women who sustained a new fragility fracture during antiresorptive therapy had a lower HRQoL score compared with patients without an incident fracture . SimilarEFOS was a large 36-month, prospective, observational study designed to evaluate fracture outcomes, back pain and HRQoL in postmenopausal women with severe osteoporosis treated with teriparatide in the outpatient setting for a maximum of 18 months, followed by a post-teriparatide treatment observational period of a further 18 months. A reduced incidence of clinical vertebral and non-vertebral fractures and reduction in back pain over 36 months has been reported elsewhere .post-hoc analysis to examine the HRQoL changes in patients grouped according to recent prior fracture in the 12 months before the baseline assessment and incident clinical fracture during 36 months follow-up.The primary aim of this paper is to present a pre-planned analysis of the HRQoL results in the EFOS study population, both during teriparatide treatment for up to 18 months and in the subsequent 18-month period after teriparatide discontinuation when patients were receiving other osteoporosis medications. In addition, we perform a secondary EFOS was a multicentre, prospective, observational study of fracture outcomes, back pain and HRQoL in postmenopausal women with osteoporosis in eight European countries ; the study design, sample size considerations, and characteristics of the patient population have been described in detail elsewhere . BrieflyAt the baseline visit, patient demographic characteristics, risk factors for osteoporosis and falls, osteoporosis therapies and disease status were recorded . The womHRQoL was measured at each visit using the EQ-5D, a generic self-administered health status questionnaire that consists of two parts . In the At the baseline assessment, a patient’s history of fragility fractures since the age of 40 years was collected by recording the fracture location and date of each fracture. From this information, a history of recent prior fracture within the last 12 months before starting teriparatide was determined and categorised as yes or no. Information on incident clinical vertebral and non-vertebral fragility fractures occurring during the study were collected at each follow-up visit as self-reported by the patient; these fractures were then diagnosed and confirmed by review of the original radiographs and/or the radiology or surgical reports at the investigational site. A new or worsened vertebral fracture was defined from the presence of a confirmed radiographic vertebral fracture associated with signs and/or symptoms suggestive of a vertebral fracture (such as acute or severe back pain). Incident morphometric spine fractures were not analysed in EFOS.Data were analysed for the total study cohort, which included all patients with a baseline visit and at least one follow-up visit. The impact of fractures on patient HRQoL was assessed in a post-hoc analysis by classifying the total study population into four mutually exclusive subgroups based on recent prior fracture in the 12 months before baseline (yes/no) and incident fracture during the study (yes/no).th and 75th percentiles for continuous variables) were used to describe the total study population and subgroups by recent prior and incident fracture status. For EQ-VAS and EQ-5D index scores, a last observation carried forward (LOCF) approach was used for missing data.Descriptive statistics  or medians with 25t-tests for other continuous variables. The p-values of the pairwise comparisons were Bonferroni adjusted.Baseline characteristics between subgroups were compared using Fisher exact tests for categorical variables, Wilcoxon rank sum tests for time since most recent fracture and number of previous fractures, and P-values for the within-group change from baseline represent the unique influence of the corresponding factor after adjustment for the other factors in the model. Pairwise comparisons between subgroups (by fracture status) in the adjusted least-squares mean change from baseline at each follow-up visit were calculated, and the p-values for the comparisons are presented.EQ-VAS changes from baseline were analysed using a mixed model for repeated measures (MMRM) with an unstructured correlation matrix and adjusting for age, duration of prior bisphosphonate treatment and a diagnosis of rheumatoid arthritis at baseline. We adjusted for age because it is associated with HRQoL . Likewisp-values within each visit are reported.For the EQ-5D index score, which was not normally distributed, Wilcoxon signed-rank test was used to assess within-group changes from baseline. Between-group comparisons used Wilcoxon rank-sum tests and Bonferroni adjusted All p-values presented are two-sided and the level of significance is set to 5%. All data were analysed using SAS software version 9.2.n = 816), 89 (10.9%) patients had an incident fracture during the study. Across the subgroups, 79–94% of patients remained in the study at 18 months and 62–78% were observed at the 36-month visit.Of the 1649 postmenopausal women enrolled in the study, 1581 were analysed at baseline and returned for at least one post-baseline visit . Figure p < 0.05); no difference was seen between patients with and without incident fracture in the groups with no recent prior fracture (groups C and D).Table p < 0.001, Wilcoxon signed rank test). Figure p < 0.001 from MMRM); the increase from baseline at 18 months was 11.3 (95%CI 9.7–12.8) and this was maintained during the post-teriparatide treatment period: 10.0 (95%CI 8.3–11.7) at 24 months and 10.7 (95%CI 8.9–12.5) at 36 months.Table post-hoc analysis, the four subgroups of patients according to recent prior and incident fracture status did not differ in their baseline mean EQ-VAS scores (Table p < 0.05 from MMRM), except for the no recent prior/incident fracture subgroup at 6, 24 and 36 months. Figure p < 0.05 for all comparisons at 18 and 36 months). Notably, the no recent prior fracture plus no incident fracture subgroup showed a clear increase in EQ-VAS from baseline to 18 months that was maintained at 36 months (as did the recent fracture plus no incident fracture subgroup). Pairwise comparisons revealed no significant differences at any visit in the change in EQ-VAS between the two subgroups with incident fractures (Groups A and C) or between the two subgroups with no incident fracture (Groups B and D) .Median Q1, Q3) EQ-5D index scores for the total study cohort increased from 0.59  at baseline to 0.73  at 18 months and were maintained at this median value after teriparatide discontinuation Table . The med EQ-5D inpost-hoc analysis, the baseline median EQ-5D index scores differed significantly between the subgroup with recent prior and incident fractures (group A) and the subgroup without recent prior and incident fractures (group D) ; all other pairwise comparisons at baseline were non-significant . Pairwise comparisons in the change from baseline at the 18 and 36 month visits showed there was significantly less improvement in EQ-5D index score in the subgroup with no recent prior/incident fracture (group C) compared with the recent prior/no incident fracture subgroup (group B) ; all other pairwise comparisons at these two time points were non-significant  is substantially improved during teriparatide treatment for up to 18 months and, importantly, is maintained during the 18-month post-teriparatide period while patients are receiving other osteoporosis treatments . NotablInterestingly, the results for the subgroup with no recent prior fracture plus no incident clinical fracture showed a low level of HRQoL at baseline and an increase during treatment. Our finding of a low baseline HRQoL even in the subgroup with no recent prior fracture is consistent with a recent systematic review, which reported that HRQoL is adversely affected by osteoporosis in the absence of vertebral fracture . HoweverOur results are consistent with a substudy from the placebo-controlled Fracture Prevention Trial (FPT) of teriparatide treatment in postmenopausal women with severe osteoporosis, which examined the associations between fractures and HRQoL measured using the Osteoporosis Assessment Questionnaire ,38. All We measured HRQoL using the generic EQ-5D questionnaire rather than an osteoporosis-specific questionnaire. EQ-5D is a validated standardised instrument for the measurement of health status. A generic instrument has advantages because it enables comparison of health effects between diseases and is the instrument of choice in health technology assessment. Previous studies using EQ-5D have shown an impaired quality of life status after fracture together with gradual improvements over the subsequent year . Thus, EAt baseline, the unadjusted mean EQ-VAS score of 52.0 for the total study cohort indicated that patients had worse quality of life compared with the German population norm for women aged 70–79 years old (mean 75.5) . We compOur results of an improvement in HRQoL during teriparatide treatment are consistent with a small retrospective single centre study of 57 patients with osteoporosis, which showed that HRQoL  improved with teriparatide treatment in a clinical practice setting . Also, tOne of the most interesting findings of the study is the influence of recent prior and incident fracture on HRQoL. We observed that women with an incident fracture had less improvement in EQ-VAS during the study than patients with no incident fracture. However, recent prior fracture in the 12 months before baseline did not seem to influence the change in HRQoL either during or after teriparatide treatment. These findings are consistent with the OSSO study, which assessed the impact of fracture on HRQoL (EQ-5D and QUALEFFO) at baseline and at 6 and 12 months of treatment with any osteoporosis medication  found noAlthough incident fracture is associated with worse HRQoL, we cannot assume a causal relationship. In our analysis of EQ-VAS we adjusted for patient age, duration of prior bisphosphonate treatment and a diagnosis of rheumatoid arthritis, but many other factors may influence HRQoL, including other comorbidities, back pain, and lifestyle .Our study has several limitations. First, this is a non-comparative study without a control group, and the subgroups of patients with incident fractures were small. The difference in sample size between the subgroups may limit the results. Second, incident fractures were those that were clinically recognised and patients could have had morphometric spine fractures not detected clinically. Third, EQ-5D assesses health status on the day of measurement and there were significant time gaps between HRQoL measurements. Fourth, the EQ-5D results may be influenced by patient drop-outs during the study. For EQ-VAS, this problem was reduced by applying the MMRM. For the other EQ-5D variables (EQ-5D index scores and domain scores), the LOCF method may have overestimated the improvement over time. Finally, comorbidities can impact on patient quality of life; although the baseline data suggests that the subgroups were reasonably well balanced regarding comorbidities.The strengths of our study include the large sample size with few eligibility restrictions, allowing recruitment of a diverse range of subjects, many of whom had comorbidities and were taking concomitant medications. Other strengths include the prospective assessment of HRQoL both during and after teriparatide discontinuation in the normal clinical practice setting, and adjustment in the analysis for factors that may influence HRQoL, such as age, duration of prior bisphosphonate treatment and a diagnosis of rheumatoid arthritis. It also shows a clinically meaningful improvement in a relevant, patient-related outcome that is consistent across all patient groups.In this large pragmatic study of postmenopausal women with severe osteoporosis, we have observed a clinically meaningful improvement in HRQoL during teriparatide treatment that is maintained after teriparatide is discontinued when most patients are receiving other osteoporosis medications. We have demonstrated that the improvement in HRQoL is unaffected by a previous history of a recent fracture in the last 12 months before starting treatment but, as expected, was attenuated by incident clinical fractures. Further studies will be needed to understand the underlying mechanisms; however, this study for the first time demonstrated that a clinically-relevant improvement in HRQoL was maintained after stopping teriparatide treatment in addition to previously demonstrated positive effects on clinical fracture. However, because of the open label and non-comparative nature of the present study, our findings need confirmation through a randomised, controlled, double-blind study.BMD: Bone mineral density; CI: Confidence interval; CNS: Central nervous system; EFOS: European Forsteo Observational Study; FPT: Fracture Prevention Trial; EQ-5D: EuroQol 5-Dimensions questionnaire; EQ-VAS: EuroQol Visual Analogue Scale; HRQol: Health-related quality of life; LOCF: Last observation carried forward; MMRM: Mixed model for repeated measures; OSSO: Observational Study of Severe Osteoporosis; RCT: Randomised controlled trial; rhPTH: Recombinant human parathyroid hormone; SD: Standard deviation.O Ljunggren has received lecture fees from, participates as a clinical investigator and is on advisory boards for Lilly, Amgen, Astra Zeneca and Nycomed. BL Langdahl has participated on advisory boards for Eli Lilly and Company, MSD, Amgen, Nycomed and Novartis, has received research grants from Eli Lilly and Company, MSD, Amgen and Novartis, and serves on Speaker’s Bureaus with Eli Lilly and Company, MSD and Amgen. WF Lems has received fees for speaking/advisory boards from MSD, Warner Chilcott, Eli Lilly, Amgen and Servier. JB Walsh has received honoraria for lectures from Servier, Eli Lilly and Company, MSD and Amgen. A Fahrleitner-Pammer has received research grants from Amgen, Eli Lilly and Company, Nycomed, Roche and Servier, and has contributed to Speaker’s Bureaus for Amgen, Daiichi Sankyo, Eli Lilly and Company, Genzyme, GSK, MSD, Novartis, Nycomed, Roche, Sanofi-Aventis and Servier. F Jakob has received honoraria for lectures and advice from Lilly, Amgen, Novartis, MSD, Nycomed, Servier and Roche, has received unrestricted research grants from Novartis, and is involved in clinical studies related to osteoporosis drugs initiated by Lilly, Amgen, Servier and Novartis. F Marin is a full-time employee and stock holder of Eli Lilly and Company. A Barrett and I Stoykov are employees of Eli Lilly and Company. D Karras and G Rajzbaum have nothing to disclose.OL, BL, WL, JW, AF, GR, FJ, DK and FM contributed to the study design, revised and approved the final version of the manuscript. AB, IS and FM contributed to the analysis plan, drafted the manuscript and read and approved the final version. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/14/251/prepub


Observational cohort study to assess the association between adherence to oral 5-aminosalicylates (5-ASAs) and all-cause costs and health care utilization among patients with active ulcerative colitis (UC) in the United States.Retrospective analysis of insurance claims from June 1997 to August 2006 in the LifeLink Database. Patient criteria: aged 18 or older with one or more claim(s) between June 1997 and August 2005 for a UC diagnosis and at least one oral 5-ASA prescription on or after the first observed UC diagnosis; continuous enrollment for at least 6 months prior to and 12 months following 5-ASA initiation (index date). As a proxy for active disease, patients needed to have at least two UC-specific non-pharmacy claims, at least 30 days of 5-ASA treatment and at least one corticosteroid prescription within the 12-month post-index period. Cumulative exposure to oral 5-ASAs over the 12-month period was calculated using the medication possession ratio (MPR). Patients with an MPR of at least 0.80 were classified as adherent. All-cause medical and pharmacy resource utilization and costs were computed over the 12-month post-index period and compared between adherent and nonadherent patients.P = 0.0025) and 34% fewer emergency department admissions (P = 0.0016). Adherent patients had 25% more pharmacy prescriptions overall (P <0.0001) and 71% more UC-related pharmacy prescriptions (P <0.0001) than did nonadherent patients. Total all-cause health care utilization was 1.13 times higher for adherent patients than for nonadherent patients (P = 0.0002). After adjusting for covariates, total all-cause costs were 29% higher for nonadherent patients than for adherent patients .1,693 UC patients met study inclusion criteria: 72% were nonadherent to 5-ASA treatment  and 28% were adherent (n = 476) in the 12-month study period. Compared with nonadherent patients, adherent patients had 31% fewer hospitalizations (Approximately three-quarters of patients with active UC were not adherent with their prescribed doses of oral 5-ASA. Nonadherence was associated with higher total all-cause costs. The key driver of decreased costs among adherent patients was inpatient hospitalizations, which more than offset these patients’ expected higher pharmacy costs. Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by mucosal inflammation in the colon. Usually, UC affects individuals between 15 and 40 years of age, although it can be found among patients of any age. The annual incidence rate of UC in the United States (US) is estimated to be eight cases per 100,000 individuals. The repBecause the underlying cause is usually unclear, treatment of UC is typically aimed at first controlling inflammation and symptoms  and then maintaining that control  ,6. AccorPrevious studies have demonstrated that adherence and persistence with 5-ASAs in patients with UC is usually low. In a study using the IMS LifeLink™ database , Yen et al.  found thAlthough the significant economic burden of UC and the low rate of adherence with UC medications has been well established in the literature, the impact of adherence with oral 5-ASA therapies on health care utilization and associated costs among patients with active UC has not been widely investigated. In this study, we analyzed administrative claims data from a large managed care population in the US to examine the impact of oral 5-ASA adherence on all-cause health care utilization and costs  among adult patients with evidence of active UC.Data were extracted from the IMS LifeLink database. At the time of our study, the database included enrollment, medical, and prescription information from 75 managed care health plans covering more than 40 million unique patients and over 2 billion health care transactions in the US from 1997 to 2006. The LifeLink database comprises longitudinal insurance claims from managed care organizations in all four US geographic regions and has an age and gender distribution representative of national managed care enrollment . The LifeLink database consists of patient demographics, institutional and professional medical claims for inpatient and outpatient services, outpatient prescription drug claims, and periods of health plan enrollment (start and stop dates). Each medical claim includes date and place of service , four International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes, and cost data in the form of managed care reimbursements  for medical services and prescription drugs utilized. Medical claims in the database also include Health Care Financing Administration Common Procedure Coding System and Current Procedural Terminology Version 4 codes indicating the type of procedure (if any) provided, as well as information on provider specialty. Prescription drug claims include the National Drug Code, brand and generic name, quantity dispensed, days’ supply, strength, and paid amount for prescriptions obtained through outpatient or retail pharmacies. Data are tracked longitudinally within patients via de-identified and unique patient numbers.Due to the de-identified nature of the LifeLink database and the fact that no new data were gathered, our study was granted exemption from the Institutional Review Board at RTI International, which holds a Federal-Wide Assurance (#3331) from the US Department of Health and Human Services’ Office for Human Research Protections; RTI Health Solutions, the organization that conducted this study, is a business unit of RTI International.Our study sample was defined by selecting patients from the LifeLink database (1997–2006) who had any primary or nonprimary diagnosis of UC (ICD-9-CM 556.xx) between June 1997 and August 2005 and at least one prescription claim for an oral 5-ASA on or after the date of each patient’s first observed UC diagnosis. For each patient identified, an index date was defined as the date of the first observed prescription for an oral 5-ASA. To ensure that each patient’s index date was a reasonable marker for oral 5-ASA therapy initiation (or re-initiation after an extended break), patients included in the study sample were required to have at least 6 months of continuous health plan enrollment prior to their index date, with no evidence of 5-ASA use during that time frame. Similarly, to ensure that any observed lack of health care events following 5-ASA therapy initiation was due to a true lack of medical activity and not cessation of insurance, patients included in the study sample were required to have at least 12 months of medical and pharmacy benefits eligibility following their index date. Each patient also was required to have a minimum duration of 30 days of 5-ASA therapy during the 12-month follow-up period. Finally, patients were required to have at least one period of active disease during follow-up, which was identified by proxy as evidence of of at least two UC-specific non-pharmacy claims and at least one corticosteroid prescription within the 12-month post-index date period. Patients with Crohn’s disease (ICD-9-CM 555.xx) were excluded from the study.Patient characteristics that were measured at the index date included age, gender, geographic region, insurance payer type , and health plan type . To assess overall comorbidity burden prior to 5-ASA initiation, a Charlson Comorbidity Index (CCI) score, with Deyo adaptation for claims data, was calculated for each patient ,17. The Oral 5-ASA adherence was measured using the medication possession ratio (MPR). A systematic literature review  found thTo account for discontinuation, we defined the denominator of the MPR formula as a fixed value of 365 days  so that those patients who discontinued 5-ASA therapy completely before the end of the follow-up period would correctly have a lower MPR. The following formula was used:Note that changes in medication dose had no impact on how refill adherence was calculated. A patient who had a dose titration upward or downward would have the same adherence as a patient who remained on the same dose, as long as both patients had identical prescription refill patterns. Mean MPR and adherence rates were calculated for the overall 5-ASA class, not separately by individual 5-ASA medications. For example, if a patient switched from mesalamine to sulfasalazine, the patient’s adherence was measured as cumulative exposure to both 5-ASA drugs. Switching between two oral 5-ASA classes therefore did not impact the calculation of MPR.Patients with an MPR of less than 0.8  were classified as nonadherent. The 80% threshold for identifying adherence and nonadherence to chronic-use medications has been previously validated  and has Total health care services utilized and associated costs during the 12-month period following initiation of 5-ASA therapy were calculated. Costs were calculated from the perspective of the third-party payer and represented actual reimbursed amounts for each service rendered. Our cost data therefore did not take into account patient copayments, co-insurance, and other out-of-pocket expenses. All-cause health care utilization and costs were compared between the group of patients who were adherent to 5-ASA therapy and the group of patients who were not. Differences in baseline demographic characteristics  and comorbidity burden (CCI scores) were controlled for when calculating total adjusted all-cause health care utilization. We did not adjust for baseline, i.e., pre-index, health care costs. The adjusted all-cause health care costs were stratified by the following cost sectors: inpatient admissions, ER visits, outpatient office visits, other non-office outpatient/ ancillary visits , and prescription drugs (UC related and non-UC related). UC-related prescriptions were defined as all prescriptions for oral and rectal 5-ASAs, corticosteroids, biologics (infliximab), immunosuppressants, and select antibiotics (ciprofloxacin and metronidazole). All cost estimates were adjusted to 2010 US dollars, using the medical care component of the US Consumer Price Index .All analyses were carried out using SAS (Version 9.1.3) statistical software package . Descriptive analyses entailed the tabular display of the mean value, standard deviation, median, and range of continuous variables of interest and the frequency distribution of categorical variables of interest. For descriptive analyses, chi-squared tests for dichotomous variables and paired t-tests for continuous variables were used to assess statistical differences in the outcomes of interest across all patients, stratified by adherence status.Multivariable regression analyses were performed to assess differences in all-cause health care utilization and costs between 5-ASA adherent and nonadherent UC patients after controlling for patient demographic characteristics and baseline comorbidity burden. The type of multivariable model estimated depended on the nature of the outcome that was assessed. For count data, outcomes such as number of inpatient admissions and outpatient office visits were used. Poisson regression models were used to compare the rate of resource utilization between the two cohorts. These models provided incidence rate ratios (IRRs), which were obtained by exponentiating the coefficients from each model estimated. The magnitude of the IRR describes the incidence rate of utilization  for patients adherent to 5-ASA therapy as a multiple of the utilization incidence rate among nonadherent patients. For example, an estimated IRR of 0.5 for a binary covariate defining nonadherence  suggests that patients who were adherent with 5-ASA therapy had 50% fewer hospitalizations than patients who were nonadherent to 5-ASA therapy.To assess differences in health care costs between the two study cohorts, a multivariable generalized linear model (GLM) framework was used, with a log-link function and a gamma distribution for the error term to resolve the issue of skewed cost distribution often reported in health care cost data. In comparison with ordinary linear regression involving log-transformed cost data, the GLM methodology offers several advantages, primarily because it estimates covariate-adjusted predicted mean costs on a dollar scale, which can then be compared using Student’s t-test -26. The We identified 99,842 patients in the LifeLink database who had at least one primary or nonprimary diagnosis code for UC (ICD-9-CM 556.xx) between June 1997 and August 2005. Nearly 60% of these patients  did not have any pharmacy claims for oral 5-ASA therapy and therefore were excluded. The final study sample consisted of 1,693 patients who met all study inclusion and exclusion criteria. Figure Table P = 0.0090), with no difference in average age between the two groups. A slightly larger percentage of patients in the adherent group resided in the Midwest than did the nonadherent group . Further, adherent patients had a greater baseline comorbidity than did non-adherent patients .The majority of UC patients (72%) were nonadherent to oral 5-ASA therapy  during the 12-month study period. Adherent patients were more likely to be male than were nonadherent patients  fewer hospitalizations and 34%  fewer ER admissions than did nonadherent patients. Patients who were adherent had 25% more pharmacy prescriptions overall. Adherent patients also had 71% more UC-related pharmacy prescriptions than did nonadherent patients, but the number of non–UC-related prescriptions did not differ between the two groups. The total number of all-cause health care visits across all cost sectors  was 1.13 times higher for adherent patients than for nonadherent patients .Table Table In this study, we examined the association between adherence to 5-ASA therapy and overall health care utilization and costs among patients with active UC. We estimated that only 28% of the UC patients on 5-ASAs who were included in the study were adherent to treatment. This finding was consistent with previous studies that have found adherence with 5-ASAs to be fairly low (range: 15% to 22%1). We alsWhile our data source presents unique advantages in assessing medication adherence and associated outcomes, our study is subject to several limitations inherent in most analyses of retrospective claims data. Therapy may be interrupted for clinically appropriate reasons, such as side effects associated with 5-ASAs and abnormal laboratory results. If this occurred, the calculated MPR would underestimate actual adherence rates. We also assumed complete medication ingestion, but patients may have disposed of medication prior to refill or stockpiled medication for future use . This woIn conclusion, this study finds adherence to oral 5-ASAs to be suboptimal and that patients who are nonadherent to therapy have greater health care costs. Efforts to promote oral 5-ASA adherence in patients with UC may lead to cost-savings for third-party payers and other stakeholders.aAt the request of the health services with which we worked, we have been asked to use this term to refer to our informants in order to ensure anonymity.Debanjali Mitra and Keith L. Davis are employees of RTI Health Solutions, an independent contract research organization that received research funding from Shire for this study. Dr. Paul Hodgkins and Linnette Yen are employees of Shire and own stock in the company. Dr. Russell D. Cohen is employed at the University of Chicago Medical Center and serves as a consultant to Shire. The author(s) declare that they have no other competing interests.Debanjali Mitra, Dr. Paul Hodgkins, and Linnette Yen were the primary developers of the study design and contributed to analysis and interpretation of results as well to the development of this manuscript. As principal investigator, Debanjali Mitra had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Debanjali Mitra and Keith L. Davis led all statistical analyses. Debanjali Mitra also served as the primary writer in drafting the manuscript text and in interpreting the results. Dr. Russell D. Cohen provided medical and clinical advice to refine and validate the study, and he participated in the drafting of the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-230X/12/132/prepub


Multi-marker molecular assays have impacted management of early stage breast cancer, facilitating adjuvant chemotherapy decisions. We generated prognostic models that incorporate protein-based molecular markers and clinico-pathological variables to improve survival prediction.We used a quantitative immunofluorescence method to study protein expression of 14 markers included in the Oncotype DX™ assay on a 638 breast cancer patient cohort with 15-year follow-up. We performed cross-validation analyses to assess performance of multivariate Cox models consisting of these markers and standard clinico-pathological covariates, using an average time-dependent Area Under the Receiver Operating Characteristic curves and compared it to nested Cox models obtained by robust backward selection procedures.A prognostic index derived from of a multivariate Cox regression model incorporating molecular and clinico-pathological covariates  is superior to models based on molecular studies alone or clinico-pathological covariates alone. Performance of this composite model can be further improved using feature selection techniques to prune variables. When stratifying patients by Nottingham Prognostic Index (NPI), the most prognostic markers in high and low NPI groups differed. Similarly, for the node-negative, hormone receptor-positive sub-population, we derived a compact model with three clinico-pathological variables and two protein markers that was superior to the full model.Prognostic models that include both molecular and clinico-pathological covariates can be more accurate than models based on either set of features alone. Furthermore, feature selection can decrease the number of molecular variables needed to predict outcome, potentially resulting in less expensive assays. Adjuvant systemic therapy for patients with breast cancer includes chemotherapy, anti-hormonal therapy and molecular targeted therapy. Selection of anti-hormonal and molecular targeted therapy is based on biological factors of individual tumors  2). The decision whether to give chemotherapy and specifics of the chemotherapy regimens used are typically based on standard clinical and pathologic criteria , in addition to receptor status. Given the variability in outcome in each risk category, much effort has been made to improve risk assessment strategies .Assays that provide prognostic information to early stage breast cancer patients to eliminate unnecessary use of chemotherapy have been developed and validated. Among the breast cancer multi-marker predictors, two are fully commercialized; the RT-PCR-based Oncotype DX™ assay  -6 and thThe Oncotype assay uses mRNA extracted from paraffin-embedded tumors to measure levels of 16 markers . It has Breast cancer tissue microarrays (TMAs) were constructed as previously described . A cohorBy standard immunohistochemistry (IHC), estrogen receptor (ER) was positive in 52%, progesterone receptor (PR) in 46% and HER2 in 14% of specimens. Of those sampled, 26% were nuclear grade 3/3, 48% were nuclear grade 2/3, 18% were nuclear grade 1/3 and for 8% of the specimens nuclear grade score was missing. The mean tumor size was 2.9 cm and 59% were larger than 2 cm. A total of 72% were invasive ductal carcinoma, 14% were lobular carcinoma, and 14% had mixed or other histology. Specimens were resected between 1962 and 1983, and follow-up was between 4 months and 53 years (mean 12.6 years). Age at diagnosis was 24 to 88 years (mean 58 years).Complete treatment history was not available for all patients. Most were treated with local irradiation. Node-negative patients were not given adjuvant systemic therapy. A minority of node-positive patients (about 15%) received chemotherapy, and about 5.6% received tamoxifen .Staining was performed for AQUA analysis as previously described . PrimaryImages were acquired for AQUA, as extensively described previously . BrieflyP < 10-90 for all three variables, . As pathologic values for ER, PR and HER2 by IHC are typically readily available at the time of initial diagnosis of breast cancer at no additional cost, the results described in this paper use the pathologist scores only. We constructed multivariate Cox proportional hazards models to analyze this set of protein markers in addition to standard clinical markers, which included ER, PR and HER2 obtained using standard IHC. We derived models predictive of 15-year breast cancer-specific survival. We performed these analyses for three different marker sets: the set of 14 markers, where the levels of ER, PR and HER2 were obtained using standard IHC and other markers by AQUA; the combination of these 14 protein markers  with the remaining four clinico-pathological variables - nodal status, tumor size, nuclear grade, and age; and the seven clinico-pathological variables - nodal status, tumor size, nuclear grade, age, ER, PR and HER2. We binarized patient age at 50 years.We measured protein levels of 14 of the 16 oncotype markers. Strong correlations were found between ER, PR and HER2 scores generated by pathologist IHC-based scoring. The significance for the Spearman correlations for ER, PR and HER2 are The AQUA scores and IHC variables were not normally distributed, as expected. For example, HER2 IHC scores were predominantly negative, and the AQUA scores for the HER2 adaptor protein GRB7 were predominantly low. This is consistent with what is known about the biology of these markers, and we therefore used the raw average of scores for all markers.The number of cases  in the standard, clinically-used low, intermediate and high Nottingham Prognostic Index (NPI) groups of our cohort is 124, 265, and 120, respectively. To increase sample size we split the cohort binarizing patients by an NPI of 4.4. We performed Cox proportional hazards analyses on these two subpopulations using the 18 protein and clinico-pathological variables.To accomplish model size reduction via feature selection and assess performance of models in an unbiased fashion, we employed a nested cross-validation procedure -20. SpecTo prevent overfitting, we effectively partitioned the data into three: a feature extraction training subset (inner training set); a model size selection and variable stability evaluation subset (inner testing set); and an outer test set for performance estimation of models trained on the outer training set, which comprised the inner training and testing sets. Specifically, we partitioned the data into 10 non-overlapping, balanced subsets of cases (outer folds). Following a standard n-fold cross-validation approach, each fold was used once as the outer testing set where the remaining folds were used as the outer training set. Similarly, at each iteration of the outer 10-fold cross-validation we partitioned the data of the outer training folds  into 10 folds to be used in an inner 10-fold cross validation loop.We used the inner training set to train reduced nested Cox models with decreasing numbers of variables from n-1 variables to one variable. These nested models were determined by a backward feature elimination procedure that iteratively removed variables with the smallest contribution to the model likelihood. We then used the inner test fold to compute the inner performance score for each of the nested models trained on the inner training folds and selected the reduced model with the highest score. The performance score of these Cox models was evaluated using the area under the staircase receiver operator characteristic curves (AUCROC) at the time of each event in the testing set and we averaged these AUCROCs across all these events. We refer to this measure as the average time-dependent AUCROCs across all death events. The average time-dependent AUCROC measure is a variant of the weighted average of time-dependent ROC curve approaches -23. We cEach iteration of the inner 10-fold cross-validation returns one reduced model. We used these 10 reduced models to compute the expected model size. The expected model size is the weighted average of the size of these models using as weights their respective inner average time-dependent AUCROCs. Similarly, the stability of each variable was determined as the fraction of reduced models containing the variable; to take performance into account we defined an alternative variable stability score by summing the average time-dependent AUCROCs of the reduced models that include the variable.For each iteration of the outer 10-fold cross-validation we used the outer training set to train: a reduced Cox model consisting of the expected model size number of variables with the largest variable stability score; and a full Cox model comprising all variables. Finally, the full and reduced models are assessed both on the outer training and testing sets  we applied two-sided Mann-Whitney U-tests.P < 10-10). The performances of the full models are shown in Figure P < 10-10) and significantly higher than the mean of the 14-covariate protein model (P < 10-10).We employed a method of quantitative immunofluorescence to derive multivariate Cox proportional hazards models for 15-year survival. We had a total of 18 variables; 14 protein markers from the Oncotype panel  and four clinico-pathological markers. ER, PR and HER2 were assessed by IHC. Many of these variables were univariately prognostic as shown in Table We sought to simplify the three models . We employed stability-based backward feature selection (described above) to derive compact Cox proportional hazards models nested within each of these three models. The cross-validated performances of the 18-variable  full models and reduced models selected from these 18-variables were assessed by the average time-dependent AUCROC measure, denoted by circles . The nested cross-validated procedure culminates in a final model that excludes BAG1, PR, GRB7, ER, BIRC5, nuclear grade, MMP11 and KI67. The variables retained in this model include the 10 variables with highest stability score .Application of the robust backward feature selection described above eliminated on average eight of the least robust features. The reduced models selected were assessed employing the average time-dependent AUCROC score to the external validation sets. The mean average time-dependent AUCROC distribution of these reduced models is 0.757, significantly higher than the corresponding distribution of the 18-variable full models (P = 7.32 × 10-9). The reduced protein-based models, although superior to the full protein-models, significantly underperform with respect to the combined protein and clinico-pathological models. These protein-only models also underperform relative to models based on standard clinico-pathological variables alone (average time-dependent AUCROC = 0.711) and its nested reduced models (average time-dependent AUCROC = 0.713), right column, Figure We similarly analyzed the same 14 proteins, but excluded the clinico-pathological variables . The average size of the 15-year survival Cox proportional hazards model . These distributions are indistinguishable in the higher NPI group (P = 0.49). Some markers such as CCNB1, KI67 and MYBL2 are not included in the lower NPI reduced model but are present in the reduced model of the higher NPI group. This indicates that one could tailor simpler/cheaper multi-protein predictors to populations stratified by clinico-pathological variables.We next sought to determine whether in each NPI category the panel of 18 markers can be reduced and whether sets of survival predictors for different NPI subpopulations vary. The number of cases with no missing values in the low, intermediate and high NPI groups was 124, 265, and 120, respectively. Due to the small sample size of the low and high NPI groups, we did not use the standard NPI cut-points of 3.4 and 5.4, but binarized the population at the midpoint of this NPI range (4.4). We applied robust backward elimination for lower and higher NPI groups . The full and reduced models of the clinico-pathological variables alone applied to this sub-population held inferior performances , hormone receptor (+) breast cancers, as many of these patients in the USA are tested using the Oncotype DX™ screen. The full model in this case consists of 17 variables, because the nodal status variable is fixed, but ER and PR variables are either positive or negative, as long as at least one of the two hormone receptors is positive. Applying robust backward selection in a nested cross-validated fashion resulted in a highly compact model consisting of five variables: AURKA, tumor size, HER2, CD68 and nuclear grade Figure . The meaWe measured protein expression levels of 14 of the 16 oncotype markers in primary tumors from 638 breast cancer patients with 15-year follow-up, using AQUA. This method has now been well established and is used by many laboratories -32. MeasOptimal staging of breast cancer patients is primarily necessary for identifying individuals in need of adjuvant chemotherapy. The seven clinico-pathological variables included in our model are typically readily available on all patients, and can be incorporated into molecular assays at no additional cost. The performance of our reduced nested models converges at a value close to 0.757 if we include both molecular and clinico-pathological covariates and drops to 0.651 if we exclude the clinico-pathological variables. Oncotype assays by RT-PCR of the 16 molecular variables in other patient cohorts are reportedly associated with AUCROCs in the same range. For example, using the oncotype RS, Goldstein et al. found that for recurrence at five-years, ROC analysis results in an AUCROC of 0.69 . Direct The performance of our reduced models suggests that we can considerably simplify our original models of 18 variables. The expected model size with the highest performance level consists of 10 of the most robust predictive variables and is comprised of four clinico-pathological variables and six additional proteins: nodal status, tumor size, AURKA, BCL2, age, CD68, HER2, MYBL2, CCNB1 and GSTM1. Thus, use of a smaller subset of variables can further decrease the cost of molecular testing.Further extension of this approach by sub-setting the cohort into low- and high-risk groups using an NPI score of 4.4, which is readily available after standard surgery at no additional cost, revealed that the marker subset with optimal performance in the lower NPI group was different than the subset in the higher NPI group. The seven variables in the reduced model for the lower NPI overlap only in part with the 11 variables in the reduced model of the higher NPI group. The reduced model of the node(-) and hormone receptor (+) subpopulation consists of only five variables, of which three are proteins .In our cohort, addition of clinico-pathological variables to the proteins associated with quantitative RT-PCR Oncotype test added significant prognostic value to the proteins alone. A compact model based on a subset of these proteins and clinical variables is superior to the entire model. Marker subsets with the highest prognostic ability in high- and low-risk NPI categories are not identical, therefore personalization of this type of assay based on readily available clinico-pathological variables can result in cost reduction without compromising accuracy.AQUA: automated quantitative analysis; AUCROC: area under the receiver operator characteristic curve; ER: estrogen receptor; HER: human epidermal growth factor receptor; IHC: Immunohistochemistry; NPI: Nottingham Prognostic Index; PR: progesterone receptor; RT-PCR: reverse transcription polymerase chain reaction; TMA: tissue microarray.Drs. Camp and Rimm are founders, stockholders, and consultants to HistoRx, a private corporation to which Yale University has given exclusive rights to produce and distribute software and technologies embedded in AQUA; Yale University retains patent rights for the AQUA technology. Dr. Rimm is also a stockholder and consultant to Metamark Genetics Inc.YK and HK initiated the project. FP, AG and YK performed all the computational aspects of the projects. YK, HK and FP drafted the manuscript. YN performed the AQUA experiments and preprocessed the data. RLC and DLR developed the AQUA technology and provided the analysis for HER2, ER and PR. All authors read and approved the manuscript.