Gingival bleeding is a useful clinical feature in the diagnosis of hereditary bleeding disorders in children.

The search for hereditary bleeding disorders (HBD) prior to invasive procedures in children is primarily based on personal and family bleeding history. Although several scores are available, they have only been evaluated in specific situations or in adults. Our monocentric retrospective study aimed to analyze the association between clinical history and four scores (HEMSTOP, PBQ, ISTH-BAT, TOSETTO) and the diagnosis of MHC in children referred to the University Hospital of Montpellier for hemostasis investigations. A total of 117 children were retrospectively included in the study. Of these, 57 (49%) were diagnosed with HBD, with 30 having primary bleeding disorders and 27 having coagulation disorders. The diagnosis of HBD was significantly associated with gingival bleeding, which was present in 30% of HBD patients. In our population, only the HEMSTOP score showed an association with the diagnosis of HBD, but it was positive in only 48% of patients. By including gingival bleeding as a factor, we modified the HEMSTOP score, which increased its sensitivity from 0.45 to 0.53. When examining primary bleeding disorders, the modified HEMSTOP score, with the inclusion of gingival bleeding, enables us to diagnose 63% of patients (see Fig. 1).    Conclusion: Therefore, gingival bleeding should be considered a useful factor in bleeding history for HBD diagnosis. Adding this symptom to a screening score such as HEMSTOP improves its sensitivity. To confirm our findings, a prospective study is required.    Trial registration: Study registration number: NCT05214300. What is Known: • Screening for hereditary bleeding disorder diseases is a necessity and a challenge in children. • Minor disorders of primary hemostasis are the most common, but often escape standard coagulation tests. What is New: • Gingival bleeding is a frequent symptom that is easy to investigate and may point to a primary hemostasis disorder. • Adding the gingival bleeding item to a routine screening score such as HEMSTOP improves sensitivity.

SPARC in cancer-associated fibroblasts is an independent poor prognostic factor in non-metastatic triple-negative breast cancer and exhibits pro-tumor activity.

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and lacks specific targeted therapeutic agents. The current mechanistic evidence from cell-based studies suggests that the matricellular protein SPARC has a tumor-promoting role in TNBC; however, data on the clinical relevance of SPARC expression/secretion by tumor and stromal cells in TNBC are limited. Here, we analyzed by immunohistochemistry the prognostic value of tumor and stromal cell SPARC expression in 148 patients with non-metastatic TNBC and long follow-up (median: 5.4 years). We also quantified PD-L1 and PD-1 expression. We detected SPARC expression in tumor cells (42.4%), cancer-associated fibroblasts (CAFs; 88.1%), tumor-associated macrophages (77.1%), endothelial cells (75.2%) and tumor-infiltrating lymphocytes (9.8%). Recurrence-free survival was significantly lower in patients with SPARC-expressing CAFs. Multivariate analysis showed that SPARC expression in CAFs was an independent prognostic factor. We also detected tumor and stromal cell SPARC expression in TNBC cytosols, and in patient-derived xenografts and cell lines. Furthermore, we analyzed publicly available single-cell mRNA sequencing data and found that in TNBC, SPARC is expressed by different CAF subpopulations, including myofibroblasts and inflammatory fibroblasts that are involved in tumor-related processes. We then showed that fibroblast-secreted SPARC had a tumor-promoting role by inhibiting TNBC cell adhesion and stimulating their motility and invasiveness. Overall, our study demonstrates that SPARC expression in CAFs is an independent prognostic marker of poor outcome in TNBC. Patients with SPARC-expressing CAFs could be eligible for anti-SPARC targeted therapy.

When a joint model should be preferred over a linear mixed model for analysis of longitudinal health-related quality of life data in cancer clinical trials.

BACKGROUND: Patient-reported outcomes such as health-related quality of life (HRQoL) are increasingly used as endpoints in randomized cancer clinical trials. However, the patients often drop out so that observation of the HRQoL longitudinal outcome ends prematurely, leading to monotone missing data. The patients may drop out for various reasons including occurrence of toxicities, disease progression, or may die. In case of informative dropout, the usual linear mixed model analysis will produce biased estimates. Unbiased estimates cannot be obtained unless the dropout is jointly modeled with the longitudinal outcome, for instance by using a joint model composed of a linear mixed (sub)model linked to a survival (sub)model. Our objective was to investigate in a clinical trial context the consequences of using the most frequently used linear mixed model, the random intercept and slope model, rather than its corresponding joint model. METHODS: We first illustrate and compare the models on data of patients with metastatic pancreatic cancer. We then perform a more formal comparison through a simulation study. RESULTS: From the application, we derived hypotheses on the situations in which biases arise and on their nature. Through the simulation study, we confirmed and complemented these hypotheses and provided general explanations of the bias mechanisms. CONCLUSIONS: In particular, this article reveals how the linear mixed model fails in the typical situation where poor HRQoL is associated with an increased risk of dropout and the experimental treatment improves survival. Unlike the joint model, in this situation the linear mixed model will overestimate the HRQoL in both arms, but not equally, misestimating the difference between the HRQoL trajectories of the two arms to the disadvantage of the experimental arm.

Flexible modeling of longitudinal health-related quality of life data accounting for informative dropout in a cancer clinical trial.

PURPOSE: A joint modeling approach is recommended for analysis of longitudinal health-related quality of life (HRQoL) data in the presence of potentially informative dropouts. However, the linear mixed model modeling the longitudinal HRQoL outcome in a joint model often assumes a linear trajectory over time, an oversimplification that can lead to incorrect results. Our aim was to demonstrate that a more flexible model gives more reliable and complete results without complicating their interpretation. METHODS: Five dimensions of HRQoL in patients with esophageal cancer from the randomized clinical trial PRODIGE 5/ACCORD 17 were analyzed. Joint models assuming linear or spline-based HRQoL trajectories were applied and compared in terms of interpretation of results, graphical representation, and goodness of fit. RESULTS: Spline-based models allowed arm-by-time interaction effects to be highlighted and led to a more precise and consistent representation of the HRQoL over time; this was supported by the martingale residuals and the Akaike information criterion. CONCLUSION: Linear relationships between continuous outcomes (such as HRQoL scores) and time are usually the default choice. However, the functional form turns out to be important by affecting both the validity of the model and the statistical significance. TRIAL REGISTRATION: This study is registered with ClinicalTrials.gov, number NCT00861094.

Joint modelling with competing risks of dropout for longitudinal analysis of health-related quality of life in cancer clinical trials.

PURPOSE: Health-related quality of life (HRQoL) is an important endpoint in cancer clinical trials. Analysis of HRQoL longitudinal data is plagued by missing data, notably due to dropout. Joint models are increasingly receiving attention for modelling longitudinal outcomes and the time-to-dropout. However, dropout can be informative or non-informative depending on the cause. METHODS: We propose using a joint model that includes a competing risks sub-model for the cause-specific time-to-dropout. We compared a competing risks joint model (CR JM) that distinguishes between two causes of dropout with a standard joint model (SJM) that treats all the dropouts equally. First, we applied the CR JM and SJM to data from 267 patients with advanced oesophageal cancer from the randomized clinical trial PRODIGE 5/ACCORD 17 to analyse HRQoL data in the presence of dropouts unrelated and related to a clinical event. Then, we compared the models using a simulation study. RESULTS: We showed that the CR JM performed as well as the SJM in situations where the risk of dropout was the same whatever the cause. In the presence of both informative and non-informative dropouts, only the SJM estimations were biased, impacting the HRQoL estimated parameters. CONCLUSION: The systematic collection of the reasons for dropout in clinical trials would facilitate the use of CR JMs, which could be a satisfactory approach to analysing HRQoL data in presence of both informative and non-informative dropout. TRIAL REGISTRATION: This study is registered with ClinicalTrials.gov, number NCT00861094.

The importance of using ordinal scores for patient classification based on health-related quality of life trajectories.

Changes in health-related quality of life (HRQoL) over time are not necessarily homogeneous within a population of interest. Our study aim was twofold: to determine homogeneous patient subpopulations distinguished by HRQoL trajectories, and to identify the particular patient profile associated with each subpopulation. To classify patients according to HRQoL dimension scores, we compared mixtures of linear mixed models (LMMs) classically applied to scores defined by the EORTC procedure, and mixtures of random effect cumulative models (CMs) applied to scores treated as ordinal variables. A simulation study showed that the mixture of LMMs overestimated the number of subpopulations and was less able to correctly classify patients than the mixture of CMs. Considering HRQoL scores as ordinal rather than continuous variables is relevant when classifying patients. The mixture of CMs for ordinal scores is able to identify homogeneous subpopulations and their associated trajectories. The application focused on changes over time in HRQoL data (collected using the EORTC QLQ-C30 questionnaire) from 132 breast cancer patients from the Moral study. Once the classification is obtained only from HRQoL scores, class membership was then explained through a logistic regression model, given a large panel of variables collected at baseline. Analysis of data revealed that deterioration over time of role functioning and insomnia was closely related to patient anxiety: anxiety at baseline is a prognostic factor for a poor level and/or a deterioration over time of HRQoL. For functional dimensions, large tumor size and high education level were associated with worse HRQoL scores.

Serum glial fibrillary acidic protein is a predictor of brain metastases in patients with metastatic breast cancer.

In patients with metastatic breast cancer (MBC), brain metastases (BM) are associated with high morbidity and mortality. However, there is no validated serum biomarker that accurately predicts BM occurrence in these patients, and the role of serum biomarkers for prognosis remains unclear. Here, we evaluated the association of neurofilament light chain (NfL), ubiquitin C-terminal hydrolase L1 (UCHL1), glial fibrillary acidic protein (GFAP) and tau serum levels with BM presence and prognosis in patients with MBC. In serum samples from patients with MBC with (n = 100) and without BM (n = 47), we measured the biomarker serum levels using single molecule array (Simoa) technology (Neurology-4-Plex assay). To evaluate their accuracy to identify patients with BM, we determined the receiver operating characteristic curve and the area under the curve (AUC) for each biomarker and calculated their sensitivity and specificity. The median serum levels of NfL, UCHL1, tau and GFAP were significantly higher in patients with BM. The AUC for GFAP (0.82, 95% confidence interval [CI] 0.75-0.88) was significantly higher than those of the other biomarkers considered independently. Using the medians as cutoff values, elevated serum levels of NfL, UCHL1, tau and GFAP were associated with BM in univariate analysis, but only high GFAP levels in multivariate analysis (odd ratio 23.4, 95% CI 6.8-80.5, P < .001). Elevated serum GFAP levels were independently associated with poor outcome. GFAP outperforms NfL, UCHL1 and tau as diagnostic and prognostic factor of BM in patients with MBC. These results must now be validated in an independent cohort of patients.

Phase II study evaluating the association of gemcitabine, trastuzumab and erlotinib as first-line treatment in patients with metastatic pancreatic adenocarcinoma (GATE 1).

In a previous phase II study (THERAPY), cetuximab and trastuzumab combination, as second-line after progression with gemcitabine, showed disease stabilization in 27% of 33 patients with pancreatic carcinoma. In the present phase II multicenter study, we assessed the efficacy and tolerance of gemcitabine, trastuzumab plus erlotinib as first-line treatment of metastatic pancreatic cancer. The primary endpoint was disease control rate (DCR, RECIST v.1); secondary endpoints were progression-free (PFS), overall (OS) survival and toxicity (NCI-CTCAE v3.0). Ancillary study addressed the predictive value of both EGFR/HER2 expression and KRAS mutational status. Sixty-three patients from four centers were included (62 evaluable for toxicity, 59 for efficacy), median age was 62 years (35-77), 59.7% men. The median treatment duration was 16.1 weeks (2.1-61). Eleven patients (19%) reported a partial tumor response, and 33 (56%) disease stabilization. DCR was 74.6% (95%CI: 61.8-85.0; 44/59 patients). After a median follow-up of 23.3 months (0.6-23.6), median PFS was 3.5 months (95%CI: 2.4-3.8) and median OS 7.9 months (95%CI: 5.1-10.2). PFS was significantly longer in patients with grade ≥ 2 cutaneous toxicities vs patients with grade 0-1 toxicities (HR = 0.55, 95%CI: 0.33-0.92, P = .020). Expression of EGFR and HER2 was correlated with PFS and OS in multivariate analysis; HER2 expression was correlated with the tumor response. Main severe toxicities were neutropenia (32%), cutaneous rash (37%) and thrombosis/embolisms (35.5%). This triplet combination is effective in terms of disease control, PFS and OS, and acceptable for safety. A larger study to investigate this combination compared to the standard regimen should be discussed.

FOLFIRINOX-R study design: a phase I/II trial of FOLFIRINOX plus regorafenib as first line therapy in patients with unresectable RAS-mutated metastatic colorectal cancer.

BACKGROUND: The chemotherapy triplet FOLFOXIRI combined to the anti-VEGF antibody bevacizumab is an option in selected patients with metastatic colorectal cancer. In this setting, RAS-mutated metastatic colorectal cancer do not benefit the same from treatment than RAS-wildtype metastatic colorectal cancer do. Together with its antiangiogenic properties, the tyrosine-kinase inhibitor regorafenib has also anti-proliferative activities whatever the RAS status is. The present trial aims at studying the safety and the efficacy of regorafenib in combination with FOLFIRINOX - a chemotherapy triplet using a different dosing schedule than FOLFOXIRI - in patients with RAS-mutated metastatic colorectal cancer. METHODS: FOLFIRINOX-R is a prospective, multicentric, non-randomised, dose-finding phase 1-2 trial. The primary endpoints are the determination of the maximum tolerated dose, the recommended phase 2 dose, and the proportion of patients achieving disease control at 48-weeks. Phase 1 follows a 3 + 3 design (12 to 24 patients to be included). Sixty nine patients will be necessary in phase 2, including 5% non-evaluable ones, with the following assumptions, one-stage Fleming design, α = 5%, ß = 20%, p0 = 35% and p1 = 50%. Key eligibility criteria include Eastern Cooperative Oncology Group Performance Status of ≤1 and RAS-mutated metastatic colorectal cancer not amenable to surgery with curative intent and not previously treated for metastatic disease. FOLFIRINOX (oxaliplatin 85 mg/m2, folinic acid 400 mg/m2, irinotecan 150-180 mg/m2, 5-fluorouracil: 400 mg/m2 then 2400 mg/m2 over 46 h) is administered every 14 days. Regorafenib (80 to 160 mg, as per dose-level) is administered orally, once daily on days 4 to 10 of each cycle. DISCUSSION: FOLFIRINOX-R is the first phase I/II study to evaluate the safety and efficacy of regorafenib in combination with FOLFIRINOX as frontline therapy for patients with RAS-mutated metastatic colorectal cancer. TRIAL REGISTRATION: EudraCT: 2018-003541-42 ; ClinicalTrials.gov: NCT03828799 .

Longitudinal analysis of health-related quality of life in cancer clinical trials: methods and interpretation of results.

PURPOSE: Health-related quality of life (HRQoL) is assessed by self-administered questionnaires throughout the care process. Classically, two longitudinal statistical approaches were mainly used to study HRQoL: linear mixed models (LMM) or time-to-event models for time to deterioration/time until definitive deterioration (TTD/TUDD). Recently, an alternative strategy based on generalized linear mixed models for categorical data has also been proposed: the longitudinal partial credit model (LPCM). The objective of this article is to evaluate these methods and to propose recommendations to standardize longitudinal analysis of HRQoL data in cancer clinical trials. METHODS: The three methods are first described and compared through statistical, methodological, and practical arguments, then applied on real HRQoL data from clinical cancer trials or published prospective databases. In total, seven French studies from a collaborating group were selected with longitudinal collection of QLQ-C30. Longitudinal analyses were performed with the three approaches using SAS, Stata and R software. RESULTS: We observed concordant results between LMM and LPCM. However, discordant results were observed when we considered the TTD/TUDD approach compared to the two previous methods. According to methodological and practical arguments discussed, the approaches seem to provide additional information and complementary interpretations. LMM and LPCM are the most powerful methods on simulated data, while the TTD/TUDD approach gives more clinically understandable results. Finally, for single-item scales, LPCM is more appropriate. CONCLUSION: These results pledge for the recommendation to use of both the LMM and TTD/TUDD longitudinal methods, except for single-item scales, establishing them as the consensual methods for publications reporting HRQoL.

Quantification of HER1, HER2 and HER3 by time-resolved Förster resonance energy transfer in FFPE triple-negative breast cancer samples.

BACKGROUND: Triple-negative breast cancer (TNBC) has a worse prognosis compared with other breast cancer subtypes, and biomarkers to identify patients at high risk of recurrence are needed. Here, we investigated the expression of human epidermal receptor (HER) family members in TNBC and evaluated their potential as biomarkers of recurrence. METHODS: We developed Time Resolved-Förster Resonance Energy Transfer (TR-FRET) assays to quantify HER1, HER2 and HER3 in formalin-fixed paraffin-embedded (FFPE) tumour tissues. After assessing the performance and precision of our assays, we quantified HER protein expression in 51 TNBC specimens, and investigated the association of their expression with relapse-free survival. RESULTS: The assays were quantitative, accurate, and robust. In TNBC specimens, HER1 levels ranged from ≈4000 to more than 2 million receptors per cell, whereas HER2 levels varied from ≈1000 to 60,000 receptors per cell. HER3 expression was very low (less than 5500 receptors per cell in all samples). Moderate HER2 expression was significantly associated with higher risk of recurrence (HR = 3.93; P = 0.003). CONCLUSIONS: Our TR-FRET assays accurately quantify HER1, HER2 and HER3 in FFPE breast tumour specimens. Moderate HER2 expression may represent a novel prognostic marker in patients with TNBC.

Clinical Correlations of Programmed Cell Death Ligand 1 Status in Liquid and Standard Biopsies in Breast Cancer.

BACKGROUND: Data regarding the prognostic value of programmed cell death ligand 1 (PD-L1) expression on circulating tumor cells (CTCs) are lacking. However, CTCs could represent an alternative approach to serial biopsies, allowing real-time monitoring of cancer phenotype. METHODS: We evaluated, in a dedicated prospective clinical trial, the clinicopathological correlations and prognostic value of PD-L1(+)-CTCs in 72 patients with metastatic breast cancer (MBC). RESULTS: Eighteen of 56 patients with available archival tissue presented at least one positive (≥1%) PD-L1 tumor sample. Baseline CTCs and PD-L1(+)-CTCs were detected in 57 (79.2%) and 26 (36.1%) patients. No significant correlation was found between PD-L1 tumors and CTC expression. In univariate analysis, triple negative (TN) phenotype, number of metastatic treatments, >2 metastatic sites, ≥5 CTCs and PD-L1(+)-CTCs were significantly associated with progression-free survival, while tissue PD-L1 expression was not. In multivariate analysis, TN phenotype, number of metastatic treatments and of metastatic sites were the only 3 variables independently associated with progression-free survival. Progesterone receptor negativity, TN phenotype, >2 metastatic sites and ≥5 CTCs were significantly associated with overall survival in univariate analysis. In multivariable analysis, TN phenotype and >2 metastatic sites were the only 2 independent variables. CONCLUSIONS: Unlike PD-L1(+)-tumor, PD-L1(+)-CTCs correlate to survival in MBC. Reappraisal of the role of PD-L1 expression by tumor tissue and by CTCs under anti-PD-1/PD-L1 treatment is necessary to evaluate its predictive value and potential role as a stratifying factor in strategies and trials for MBC patients with MBC. CLINICAL TRIAL REGISTRATION: NCT02866149.

Impact of single-nucleotide polymorphisms in DNA repair pathway genes on response to chemoradiotherapy in rectal cancer patients: Results from ACCORD-12/PRODIGE-2 phase III trial.

We examined whether 66 germline single-nucleotide polymorphisms (SNPs) in 10 candidate genes would predict clinical outcome in 316 patients with resectable locally advanced rectal cancer (LARC) enrolled in the ACCORD-12 phase III trial who were randomly treated with preoperative radiotherapy plus capecitabine (CAP45; n = 155) or dose-intensified radiotherapy plus capecitabine and oxaliplatin (CAPOX50; n = 161). The primary endpoint was tumor response according to the Dworak score. Multivariate logistic regression models adjusted on treatment arm and T stage determined the SNPs prognostic and predictive values for tumor response. In univariate analysis, five SNPs in ERCC2, XPA, MTHFR and ERCC1 were associated with the Dworak score in the CAPOX50 arm. In the overall population, interaction with treatment arm was significant for ERCC2 rs1799787 (pinteraction = 0.05) and XPA rs3176683 (pinteraction = 0.008), suggesting a predictive effect for response to oxaliplatin-based chemoradiotherapy (CRT). All but XPA rs3176683 had a prognostic effect on tumor response. In a multivariate model, interaction remained significant for XPA rs3176683 ([OR 7.33, 95% CI 1.40-38.23], pinteraction = 0.018) and the prognostic effect significant for ERCC2 rs1799787 ([OR 0.55, 95%CI 0.32-0.93], p = 0.027) and ERCC1 rs10412761 ([OR 0.57, 95%CI 0.34-0.98], p = 0.042). Patients with the T/G haplotype of rs1799787 and rs10412761 had a 60% decrease in odds of response (p < 0.001). None of the five SNPs were associated with toxicity, overall and disease-free survival. These data suggest that genetic variation in DNA repair genes influences response to preoperative CRT in LARC and identify patients who benefit from the addition of oxaliplatin to CRT.

Strategies for clinical development of monoclonal antibodies beyond first-in-human trials: tested doses and rationale for dose selection.

BACKGROUND: Our previous survey on first-in-human trials (FIHT) of monoclonal antibodies (mAbs) showed that, due to their limited toxicity, the recommended phase II dose (RP2D) was only tentatively defined. METHODS: We identified, by MEDLINE search, articles on single-agent trials of mAbs with an FIHT included in our previous survey. For each mAb, we examined tested dose(s) and dose selection rationale in non-FIHTs (NFIHTs). We also assessed the correlation between doses tested in the registration trials (RTs) of all FDA-approved mAbs and the corresponding FIHT results. RESULTS: In the 37 dose-escalation NFIHTs, the RP2D indication was still poorly defined. In phase II-III NFIHTs (n=103 on 37 mAbs), the FIHT RP2D was the only dose tested for five mAbs. For 16 mAbs, only doses different from the FIHT RP2D or the maximum administered dose (MAD) were tested and the dose selection rationale infrequently indicated. In the 60 RTs on 27 FDA-approved mAbs with available FIHT, the FIHT RP2D was tested only for two mAbs, and RT doses were much lower than the FIHT MAD. CONCLUSIONS: The rationale beyond dose selection in phase II and III trials of mAbs is often unclear in published articles and not based on FIHT data.

Prognostic value of androgen receptor and FOXA1 co-expression in non-metastatic triple negative breast cancer and correlation with other biomarkers.

BACKGROUND: In luminal androgen receptor (AR) tumours, FOXA1 may direct AR to sites occupied by ER in luminal tumours, thus stimulating proliferation. METHODS: AR and FOXA1 expression were evaluated by immunohistochemistry in 333 non-metastatic triple-negative breast cancers (TNBC). Positivity threshold was set at ≥ 1% staining. Lymphocytic infiltration, PD-L1expression, PIK3CA mutations, PTEN defects and BRCA1 promoter methylation were assessed. RESULTS: AR + /FOXA1 + tumours (42.4%) were more frequently: found in older patients, lobular, of lower nuclear grade, with more frequently PIK3CA mutations; exhibited less frequently BRCA1 promoter methylation, defects of PTEN and PD-L1 expression than others. Recurrence-free and overall survivals were significantly lower for AR + /FOXA1 + TNBC (median follow-up: 7.8 years). CONCLUSIONS: AR + /FOXA1 + expression defines a luminal-like TNBC subgroup affected with a worse outcome compared to other TNBC and a higher risk of late recurrences. This subgroup appears enriched in PIK3CA mutations, suggesting a role for PI3K inhibitors in this subgroup.

Rational development of synergistic combinations of chemotherapy and molecular targeted agents for colorectal cancer treatment.

BACKGROUND: The irinotecan-induced phosphokinome changes in colorectal cancer (CRC) cells were used to guide the selection of targeted agents to be tested in combination with irinotecan. METHODS: Phosphokinome profiling with peptide arrays of tumour samples from nude mice xenografted with HT29 cells and treated or not with an effective dose of irinotecan was used to identify signalling pathways activated by irinotecan treatment. Then, drugs targeting these pathways were combined in vitro with irinotecan to test potential synergistic effect. The interactions between these drug combinations were assessed by a dose matrix approach. Confirmation of the most potential combination has been confirmed in vivo in xenografted mice. RESULTS: Irinotecan induced in vivo the activation of AKT and MEK1 phosphorylation. The dose matrix approach showed that BKM120 (PI3K inhibitor) and MEK162 (MEK inhibitor) are synergistic in vitro and in vivo with a cytostatic and cytotoxic effect, while combination of BKM120 and irinotecan or MEK162 and irinotecan are only additive or even antagonistic. However, the triple combination of SN38, BKM120 and MEK162 showed a better synergistic effect that BKM120 and MEK162, indicating that the cells need to inhibit both AKT and ERK pathways to become more sensitive to irinotecan-based chemotherapies. CONCLUSION: Analysis of chemotherapy-induced phosphokinome changes helps to elucidate the mechanisms of drug resistance and to guide the selection of targets for combination therapies with synergistic activity.

EM algorithm estimation of a structural equation model for the longitudinal study of the quality of life.

Health-related quality of life (HRQoL) data are measured via patient questionnaires, completed by the patients themselves at different time points. We focused on oncology data gathered through the use of European Organization for Research and Treatment of Cancer questionnaires, which decompose HRQoL into several functional dimensions, several symptomatic dimensions, and the global health status (GHS). We aimed to perform a global analysis of HRQoL and reduce the number of analyses required by using a two-step approach. First, a structural equation model (SEM) was used for each time point; in these models, the GHS is explained by two latent variables. Each latent variable is a factor that summarizes, respectively, the functional dimensions and the symptomatic dimensions to the global measurement. This is achieved through the maximization of the likelihood of each SEM using the EM algorithm, which has the advantage of giving an estimation of the subject-specific factors and the influence of additional explanatory variables. Then, to consider the longitudinal aspect, the GHS variable and the two factors were concatenated for each patient visit at which the questionnaire was completed. The GHS and the two factors estimated in the first step can then be explained by additional explanatory variables using a linear mixed model.

Distribution- and anchor-based methods to determine the minimally important difference on patient-reported outcome questionnaires in oncology: a structured review.

BACKGROUND: Interpretation of differences or changes in patient-reported outcome scores should not only consider statistical significance, but also clinical relevance. Accordingly, accurate determination of the minimally important difference (MID) is crucial to assess the effectiveness of health care interventions, as well as for sample size calculation. Several methods have been proposed to determine the MID. Our aim was to review the statistical methods used to determine MID in patient-reported outcome (PRO) questionnaires in cancer patients, focusing on the distribution- and anchor-based approaches and to present the variability of criteria used as well as possible limitations. METHODS: We performed a systematic search using PubMed. We searched for all cancer studies related to MID determination on a PRO questionnaire. Two reviewers independently screened titles and abstracts to identify relevant articles. Data were extracted from eligible articles using a predefined data collection form. Discrepancies were resolved by discussion and the involvement of a third reviewer. RESULTS: Sixty-three articles were identified, of which 46 were retained for final analysis. Both distribution- and anchor-based approaches were used to assess the MID in 37 studies (80.4%). Different time points were used to apply the distribution-based method and the most frequently reported distribution was the 0.5 standard deviation at baseline. A change in a PRO external scale (N = 13, 30.2%) and performance status (N = 15, 34.9%) were the most frequently used anchors. The stability of the MID over time was rarely investigated and only 28.2% of studies used at least 3 assessment timepoints. The robustness of anchor-based MID was questionable in 37.2% of the studies where the minimal number of patients by anchor category was less than 20. CONCLUSION: Efforts are needed to improve the quality of the methodology used for MID determination in PRO questionnaires used in oncology. In particular, increased attention to the sample size should be paid to guarantee reliable results. This could increase the use of these specific thresholds in future studies.

Item response models for the longitudinal analysis of health-related quality of life in cancer clinical trials.

BACKGROUND: The use of health-related quality of life (HRQoL) as an endpoint in cancer clinical trials is growing rapidly. Hence, research into the statistical approaches used to analyze HRQoL data is of major importance, and could lead to a better understanding of the impact of treatments on the everyday life and care of patients. Amongst the models that are used for the longitudinal analysis of HRQoL, we focused on the mixed models from item response theory, to directly analyze raw data from questionnaires. METHODS: We reviewed the different item response models for ordinal responses, using a recent classification of generalized linear models for categorical data. Based on methodological and practical arguments, we then proposed a conceptual selection of these models for the longitudinal analysis of HRQoL in cancer clinical trials. RESULTS: To complete comparison studies already present in the literature, we performed a simulation study based on random part of the mixed models, so to compare the linear mixed model classically used to the selected item response models. As expected, the sensitivity of the item response models to detect random effects with lower variance is better than that of the linear mixed model. We then used a cumulative item response model to perform a longitudinal analysis of HRQoL data from a cancer clinical trial. CONCLUSIONS: Adjacent and cumulative item response models seem particularly suitable for HRQoL analysis. In the specific context of cancer clinical trials and the comparison between two groups of HRQoL data over time, the cumulative model seems to be the most suitable, given that it is able to generate a more complete set of results and gives an intuitive illustration of the data.