Concomitant medication, comorbidity and survival in patients with breast cancer.

Between 30% and 70% of patients with breast cancer have pre-existing chronic conditions, and more than half are on long-term non-cancer medication at the time of diagnosis. Preliminary epidemiological evidence suggests that some non-cancer medications may affect breast cancer risk, recurrence, and survival. In this nationwide cohort study, we assessed the association between medication use at breast cancer diagnosis and survival. We included 235,368 French women with newly diagnosed non-metastatic breast cancer. In analyzes of 288 medications, we identified eight medications positively associated with either overall survival or disease-free survival: rabeprazole, alverine, atenolol, simvastatin, rosuvastatin, estriol (vaginal or transmucosal), nomegestrol, and hypromellose; and eight medications negatively associated with overall survival or disease-free survival: ferrous fumarate, prednisolone, carbimazole, pristinamycin, oxazepam, alprazolam, hydroxyzine, and mianserin. Full results are available online from an interactive platform ( https://adrenaline.curie.fr ). This resource provides hypotheses for drugs that may naturally influence breast cancer evolution.

Early morning immune checkpoint blockade and overall survival of patients with metastatic cancer: An In-depth chronotherapeutic study.

INTRODUCTION: Recent retrospective studies suggest potential large patient's benefit through proper timing of immune checkpoint blockers (ICB). The association between ICB treatment timing and patient survival, neoplastic response and toxicities was investigated, together with interactions with performance status (PS) and sex. METHODS: A cohort of patients with metastatic or locally advanced solid tumors, who received pembrolizumab, nivolumab, atezolizumab, durvalumab, or avelumab, alone or with concomitant chemotherapy, between November 2015 and March 2021, at the Centre Leon Bérard (France), was retrospectively studied. RESULTS: 361 patients were investigated (80% non-small cell lung cancer patients, mean [SD] age: 63 [11] years, 39% of women, 83% PS0-1 at first infusion, 19% received concomitant chemotherapy). ICB were administered from 07:25 to 17:21 and optimal morning/afternoon cut-off was 11:37. Morning infusions were associated with increased OS as compared to afternoon (median 30.3 vs 15.9 months, p = 0.0024; HR 1.56 [1.17-2.1], p = 0.003). A strong PS-timing interaction was found (PS0-1 patients, HR=1.53 [1.10-2.12], p = 0.011; PS2-3 patients, HR=0.50 [0.25-0.97], p = 0.042). Morning PS0-1 patients displayed increased OS (median 36.7 vs 21.3 months, p = 0.023), partial/complete response rate (58% vs 41%, p = 0.027), and grade1-3 toxicities (49% vs 34%, p = 0.028). Mortality risk ratio between infusions at worst time-of-day, estimated at 13:36 [12:48-14:23], and in early morning was equal to 4.8 ([2.3-10.1], p = 0.008). Timing differences in toxicities resulted significant only in female patients (women vs men: p < 0.001 vs 0.4). CONCLUSIONS: Early morning ICB infusion was associated with increased OS, response, and toxicities in patients with PS0-1 as compared to later infusions within the day. Prospective randomized trials are needed to confirm this retrospective study.

Systematic assessment of tumor necrosis at baseline in cervical cancer - An independent factor associated with poor outcome.

Cervical cancer (CC) is a leading challenge in oncology worldwide, with high prevalence and mortality rates in young adults, most prominent in low to middle-income countries with marginal screening facilities. From the prospectively collected BioRAIDS (NCT02428842) cohort of primary squamous CC conducted in 7 European countries, a central pathology review was carried out on 294 patients' tumors. The focus was on identification of tumor-stromal characteristics such as CD8+, CD45+, CD68+ staining cells, PD-L1 expression, tumor infiltrating lymphocytes (TILs) together with the degree of tumor necrosis. Both (FIGO-2018) stage (I-II/III-IV) as well as tumor necrosis were highly significantly associated with Progression-free Survival (PFS); with tumor necrosis scoring as most potent independent factor in a multivariable analysis (p < 0.001). Tumor necrosis can be assessed in the very first diagnostic biopsyand our data suggest that this rapid, simple and cost-effective biomarker, should be routinely assessed prior to treatment decisions.

Current perspectives for external control arms in oncology clinical trials: Analysis of EMA approvals 2016-2021.

Leveraging external control data, especially real-world data (RWD), has drawn particular attention in recent years for facilitating oncology clinical development and regulatory decision-making. Medical regulators have published guidance on accelerating the use of RWD and external controls. However, few systematic discussions have been conducted on external controls in cancer drug submissions and regulatory feedback. This study aimed to identify European oncology drug approvals using external control data to demonstrate clinical efficacy. We included 18 eligible submissions employing 24 external controls and then discussed the use of external control, data sources, analysis methods, and regulators' feedback. The external controls have been actively submitted to the European Medical Agency (EMA) recently. We found that 17 % of the EMA-approved cancer drugs in 2016-2021 used external controls, among which 37 % of the cases leveraged RWD. However, nearly one-third of the external controls were not considered supportive evidence by EMA due to limitations regarding heterogeneous patient populations, missing outcome assessment in RWD, and inappropriate statistical analysis. This study highlighted that proper use of external controls requires a careful assessment of clinical settings, data availability, and statistical methodology. For better use of external controls in oncology clinical trials, we recommend: prospective study designs to avoid selection bias, sufficient baseline data to ensure the comparability of study populations, consistent endpoint measurements to enable outcome comparison, robust statistical methodology for comparative analysis, and collaborative efforts of sponsors and regulators to establish regulatory frameworks.

Reconsidering conceptual knowledge: Heterogeneity of its components.

Cognitive arithmetic classically distinguishes procedural and conceptual knowledge as two determinants of the acquisition of flexible expertise. Whereas procedural knowledge relates to algorithmic routines, conceptual knowledge is defined as the knowledge of core principles, referred to as fundamental structures of arithmetic. To date, there is no consensus regarding their number, list, or even their definition, partly because they are difficult to measure. Recent findings suggest that among the most complex of these principles, some might not be "fundamental structures" but rather may articulate several components of conceptual knowledge, each specific to the arithmetic operation involved. Here, we argue that most of the arithmetic principles similarly may rather articulate several core concepts specific to the operation involved. Data were collected during a national mathematics contest based on an arithmetic game involving a large sample of 9- to 11-year-old students (N = 11,243; 53.1% boys) over several weeks. The purpose of the game was to solve complex arithmetic problems using five numbers and the four operations. A principal component analysis (PCA) was performed. The results show that both conceptual and procedural knowledge were used by children. Moreover, the PCA sorted conceptual and procedural knowledge together, with dimensions being defined by the operation rather than by the concept. This implies that "fundamental structures" rather regroup different concepts that are learned separately. This opens the way to reconsider the very nature of conceptual knowledge and has direct pedagogical implications.

Increased Cardiac Risk After a Second Malignant Neoplasm Among Childhood Cancer Survivors: A FCCSS Study.

Background: Childhood cancer survivors (CCS) are at an elevated risk of developing both a second malignant neoplasm (SMN) and cardiac disease. Objectives: This study sought to assess the excess of occurrence of cardiac disease after a SMN among CCS. Methods: Analyses included 7,670 CCS from the French Childhood Cancer Survivors Study cohort diagnosed between 1945 and 2000. To account for the time dependence of the occurrence of a SMN, we employed a landmark approach, considering an additive regression model for the cumulative incidence of cardiac disease. We estimated the effect of a SMN on the instantaneous risk of cardiac disease using a proportional cause-specific hazard model, considering a SMN as a time-dependent exposure. In both models, we adjusted for demographic and treatment information and considered death as a competing event. Results: In 7,670 CCS over a median follow-up of 30 years (IQR: 22-38 years), there were 378 cases of cardiac disease identified, of which 49 patients experienced a SMN. Patients who survived 25 years after their childhood cancer diagnosis and had a SMN in that time frame had a significantly increased cumulative incidence of cardiac disease, which was 3.8% (95% CI: 0.5% to 7.1%) higher compared with those without a SMN during this period. No SMN-induced excess of cardiac disease was observed at subsequent landmark times. SMNs were associated with a 2-fold increase (cause-specific HR: 2.0; 95% CI: 1.4-2.8) of cardiac disease. Conclusions: The occurrence of a SMN among CCS is associated with an increased risk of cardiac disease occurrence and risk at younger ages.

Erector spinae plane block versus thoracic paravertebral block for the prevention of acute postsurgical pain in breast cancer surgery: A prospective observational study compared with a propensity score-matched historical cohort.

BACKGROUND: Preventing acute postsurgical pain (PSP) following breast cancer surgery is a major issue. Thoracic paravertebral block (TPVB) has been widely studied for this indication. Erector spinae plane block (ESPB) has been assumed to be effective. We aimed to compare the efficacy and safety of ESPB over TPVB in preventing acute PSP. METHODS: In this prospective observational study, 120 patients admitted for unilateral major oncologic breast surgery received T2/T3 ESPB (ropivacaine 0.75%, 0.35 ml.kg-1), and 102 were analysed. Then, the ESPB cohort was compared to a TPVB cohort from the experimental arm of a randomized controlled study with the same protocol (NCT02408393) using propensity score matching analysis. The primary outcome was the need for morphine consumption in the PACU. Secondary outcomes were the morphine total dose, the incidence of ESPB and TPVB complications, and discontinuous visual analogue scale measurement trends at rest and at mobilization in the 24 hours after surgery. RESULTS: A total of 102 patients completed the study between December 2018 and August 2019. Propensity score matching formed 94 matched pairs. The proportion of morphine titration in the PACU was higher in the ESPB group than in the TPVB group (74.5% vs. 41.5%, p<0.001), with a between-group difference of 33.0% (95% CI [19.3%, 46.7%]). No ESPB-related complications were observed. CONCLUSION: ESPB is less effective in preventing morphine consumption in the PACU than TPVB. Our findings do not support the use of ESPB as the first-line regional anaesthesia for major breast cancer surgery. Randomized trials comparing ESPB and TPVB are needed.

Association between Preoperative Medication Lists and Postoperative Hospital Length of Stay after Endoscopic Transsphenoidal Pituitary Surgery.

Background: Endoscopic transsphenoidal surgery is the most common technique for the resection of pituitary adenoma. Data on factors associated with extended hospital stay after this surgery are limited. We aimed to characterize the relationship between preoperative medications and the risk of prolonged postoperative length of stay after this procedure. Methods: This single-center, retrospective cohort study included all adult patients scheduled for transsphenoidal pituitary surgery from 1 July 2016 to 31 December 2019. Anatomical Therapeutic Chemical codes were used to identify patients' preoperative medications. The primary outcome was a prolonged postoperative hospital length of stay. Secondary outcomes included unplanned admission to the Intensive Care Unit, and in-hospital and one-year mortality. We developed a descriptive logistic model that included preoperative medications, obesity and age. Results: Median postoperative length of stay was 3 days for the 704 analyzed patients. Patients taking ATC-H drugs were at an increased risk of prolonged length of stay (OR 1.56, 95% CI 1.26−1.95, p < 0.001). No association was found between preoperative ATC-H medication and unplanned ICU admission or in-hospital mortality. Patients with multiple preoperative ATC-H medications had a significantly higher mean LOS (5.4 ± 7.6 days) and one-year mortality (p < 0.02). Conclusions: Clinicians should be aware of the possible vulnerability of patients taking systemic hormones preoperatively. Future studies should test this medication-based approach on endoscopic transsphenoidal pituitary surgery populations from different hospitals and countries.

A catalog of numerical centrosome defects in epithelial ovarian cancers.

Centrosome amplification, the presence of more than two centrosomes in a cell is a common feature of most human cancer cell lines. However, little is known about centrosome numbers in human cancers and whether amplification or other numerical aberrations are frequently present. To address this question, we have analyzed a large cohort of primary human epithelial ovarian cancers (EOCs) from 100 patients. We found that rigorous quantitation of centrosome number in tumor samples was extremely challenging due to tumor heterogeneity and extensive tissue disorganization. Interestingly, even if centrosome clusters could be identified, the incidence of centrosome amplification was not comparable to what has been described in cultured cancer cells. Surprisingly, centrosome loss events where a few or many nuclei were not associated with centrosomes were clearly noticed and overall more frequent than centrosome amplification. Our findings highlight the difficulty of characterizing centrosome numbers in human tumors, while revealing a novel paradigm of centrosome number defects in EOCs.

A parametric approach to relaxing the independence assumption in relative survival analysis.

With known cause of death (CoD), competing risk survival methods are applicable in estimating disease-specific survival. Relative survival analysis may be used to estimate disease-specific survival when cause of death is either unknown or subject to misspecification and not reliable for practical usage. This method is popular for population-based cancer survival studies using registry data and does not require CoD information. The standard estimator is the ratio of all-cause survival in the cancer cohort group to the known expected survival from a general reference population. Disease-specific death competes with other causes of mortality, potentially creating dependence among the CoD. The standard ratio estimate is only valid when death from disease and death from other causes are independent. To relax the independence assumption, we formulate dependence using a copula-based model. Likelihood-based parametric method is used to fit the distribution of disease-specific death without CoD information, where the copula is assumed known and the distribution of other cause of mortality is derived from the reference population. We propose a sensitivity analysis, where the analysis is conducted across a range of assumed dependence structures. We demonstrate the utility of our method through simulation studies and an application to French breast cancer data.

Circulating HPV DNA as a Marker for Early Detection of Relapse in Patients with Cervical Cancer.

PURPOSE: Almost all cervical cancers are caused by human papillomavirus (HPV) and patients with advanced stage are at high risk for relapse. Circulating HPV DNA (HPV ctDNA) may serve as a residual tumor marker at the end of chemoradiation or to predict relapse during the follow-up period. EXPERIMENTAL DESIGN: We analyzed serum samples from 94 HPV16- or HPV18-related CCs from the BioRAIDs prospective cohort. Samples were collected before and after treatment and during an 18-month follow-up period. Using digital droplet PCR (ddPCR), we assessed the relevance of circulating HPV E7 gene as a marker for residual disease compared to HPV integration site and PIK3CA mutations. Finally, the prognostic impact of circulating HPV E7 gene was assessed with its prediction value of relapse. RESULTS: HPV E7 gene was the most sensitive tumor marker, superior to both HPV integration sites and PIK3CA mutations in serum. Circulating HPV DNA (HPV ctDNA) was detected in 63% (59/94) of patients, before treatment. HPV ctDNA detection in serum sample was associated with high FIGO stage (P = 0.02) and para-aortic lymph node involvement (P = 0.01). The level of HPV ctDNA was positively correlated with HPV copy number in the tumor (R = 0.39, P < 0.001). Complete clearance of HPV ctDNA by the end of treatment was significantly associated with a longer PFS (P < 0.0001). Patients with persistent HPV ctDNA in serum relapsed with a median time of 10 months (range, 2-15) from HPV ctDNA detection. CONCLUSIONS: HPV ctDNA detection is a useful marker to predict relapse in cervical cancer.See related commentary by Wentzensen and Clarke, p. 5733.

Total metabolic tumor volume and spleen metabolism on baseline [18F]-FDG PET/CT as independent prognostic biomarkers of recurrence in resected breast cancer.

PURPOSE: We evaluated whether biomarkers on baseline [18F]-FDG PET/CT are associated with recurrence after surgery in patients with invasive breast cancer of no special type (NST). METHODS: In this retrospective single-center study, we included consecutive patients with non-metastatic breast cancer of NST who underwent [18F]-FDG PET/CT before treatment, including surgery, between 2011 and 2016. Clinicopathological data were collected. Tumor SUVmax, total metabolic tumor volume (TMTV), and spleen- and bone marrow-to-liver SUVmax ratios (SLR, BLR) were measured from the PET images. Cut-off values were determined using predictiveness curves to predict 5-year recurrence-free survival (5y-RFS). A multivariable prediction model was developed using Cox regression. The association with stromal tumor-infiltrating lymphocytes (TILs) levels (low if <50%) was studied by logistic regression. RESULTS: Three hundred and three women were eligible, including 93 (31%) with triple-negative breast carcinoma. After a median follow-up of 6.2 years, 56 and 35 patients experienced recurrence and death, respectively. The 5y-RFS rate was 86%. In multivariable analyses, high TMTV (>20 cm3) and high SLR (>0.76) were associated with shorter 5y-RFS (HR 2.4, 95%CI 1.3-4.5, and HR 1.9, 95%CI 1.0-3.6). In logistic regression, high SLR was the only independent factor associated with low stromal TILs (OR 2.8, 95%CI 1.4-5.7). CONCLUSION: High total metabolic tumor volume and high spleen glucose metabolism on baseline [18F]-FDG PET/CT were associated with poor 5y-RFS after surgical resection in patients with breast cancer of NST. Spleen metabolism was inversely correlated with stromal TILs and might be a surrogate for an immunosuppressive tumor microenvironment.

Insights for Quantifying the Long-Term Benefit of Immunotherapy Using Quantile Regression.

PURPOSE: Immunotherapy has been approved to treat many tumor types. However, one characteristic of this therapeutic class is that survival benefit is due to late immune response, which leads to a delayed treatment effect. Quantifying the benefit, if any, of such treatment, will thus require other metrics than the usual hazard ratio and different approaches have been proposed to quantify the long-term response of immunotherapy. METHOD: In this paper, we suggest to use quantile regression for survival data to quantify the long-term benefit of immunotherapy. Our motivation is that this approach is not trial-specific and provides clinically understandable results without specifying arbitrary time points or the necessity to reach median survival, as is the case with other methods. We use reconstructed data from published Kaplan-Meier curves to illustrate our method. RESULTS: On average, patients from the immunotherapy group have 60% chance to survive 5.46 months (95% CI, 2.57 to 9.02) more than patients in the chemotherapy group.

Genetic markers and phosphoprotein forms of beta-catenin pß-Cat552 and pß-Cat675 are prognostic biomarkers of cervical cancer.

BACKGROUND: Cervical cancer (CC) remains a leading cause of gynaecological cancer-related mortality world wide and constitutes the third most common malignancy in women. The RAIDs consortium (http://www.raids-fp7.eu/) conducted a prospective European study [BioRAIDs (NCT02428842)] with the objective to stratify CC patients for innovative treatments. A "metagene" of genomic markers in the PI3K pathway and epigenetic regulators had been previously associated with poor outcome [2]. METHODS: To detect new, more specific, targets for treatment of patients who resist standard chemo-radiation, a high-dimensional Cox model was applied to define dominant molecular variants, copy number variations, and reverse phase protein arrays (RPPA). FINDINGS: Survival analysis on 89 patients with all omics data available, suggested loss-of-function (LOF) or activating molecular alterations in nine genes to be candidate biomarkers for worse prognosis in patients treated by chemo-radiation while LOF of ATRX, MED13 as well as CASP8 were associated with better prognosis. When protein expression data by RPPA were factored in, the supposedly low molecular weight and nuclear form, of beta-catenin, phosphorylated in Ser552 (pß-Cat552), ranked highest for good prognosis, while pß-Cat675 was associated with worse prognosis. INTERPRETATION: These findings call for molecularly targeted treatments involving p53, Wnt pathway, PI3K pathway, and epigenetic regulator genes. Pß-Cat552 and pß-Cat675 may be useful biomarkers to predict outcome to chemo-radiation, which targets the DNA repair axis. FUNDING: European Union's Seventh Program for research, technological development and demonstration (agreement N°304,810), the Fondation ARC pour la recherche contre le cancer.

A covariate-specific time-dependent receiver operating characteristic curve for correlated survival data.

Several studies for the clinical validity of circulating tumor cells (CTCs) in metastatic breast cancer were conducted showing that it is a prognostic biomarker of overall survival. In this work, we consider an individual patient data meta-analysis for nonmetastatic breast cancer to assess the discrimination of CTCs regarding the risk of death. Data are collected in several centers and present correlated failure times for subjects of the same center. However, although the covariate-specific time-dependent receiver operating characteristic (ROC) curve has been widely used for assessing the performance of a biomarker, there is no methodology yet that can handle this specific setting with clustered censored failure times. We propose an estimator for the covariate-specific time-dependent ROC curves and area under the ROC curve when clustered failure times are detected. We discuss the assumptions under which the estimators are consistent and their interpretations. We assume a shared frailty model for modeling the effect of the covariates and the biomarker on the outcome in order to account for the cluster effect. A simulation study was conducted and it shows negligible bias for the proposed estimator and a nonparametric one based on inverse probability censoring weighting, while a semiparametric estimator, ignoring the clustering, is markedly biased. Finally, in our application to breast cancer data, the estimation of the covariate-specific area under the curves illustrates that the CTCs discriminate better patients with inflammatory tumor than patients with noninflammatory tumor, with respect to their risk of death.

On evaluating how well a biomarker can predict treatment response with survival data.

One of the objectives of personalized medicine is to take treatment decisions based on a biomarker measurement. Therefore, it is often interesting to evaluate how well a biomarker can predict the response to a treatment. To do so, a popular methodology consists of using a regression model and testing for an interaction between treatment assignment and biomarker. However, the existence of an interaction is not sufficient for a biomarker to be predictive. It is only necessary. Hence, the use of the marker-by-treatment predictiveness curve has been recommended. In addition to evaluate how well a single continuous biomarker predicts treatment response, it can further help to define an optimal threshold. This curve displays the risk of a binary outcome as a function of the quantiles of the biomarker, for each treatment group. Methods that assume a binary outcome or rely on a proportional hazard model for a time-to-event outcome have been proposed to estimate this curve. In this work, we propose some extensions for censored data. They rely on a time-dependent logistic model, and we propose to estimate this model via inverse probability of censoring weighting. We present simulations results and three applications to prostate cancer, liver cirrhosis, and lung cancer data. They suggest that a large number of events need to be observed to define a threshold with sufficient accuracy for clinical usefulness. They also illustrate that when the treatment effect varies with the time horizon which defines the outcome, then the optimal threshold also depends on this time horizon.

A review of the use of time-varying covariates in the Fine-Gray subdistribution hazard competing risk regression model.

In survival analysis, time-varying covariates are covariates whose value can change during follow-up. Outcomes in medical research are frequently subject to competing risks (events precluding the occurrence of the primary outcome). We review the types of time-varying covariates and highlight the effect of their inclusion in the subdistribution hazard model. External time-dependent covariates are external to the subject, can effect the failure process, but are not otherwise involved in the failure mechanism. Internal time-varying covariates are measured on the subject, can effect the failure process directly, and may also be impacted by the failure mechanism. In the absence of competing risks, a consequence of including internal time-dependent covariates in the Cox model is that one cannot estimate the survival function or the effect of covariates on the survival function. In the presence of competing risks, the inclusion of internal time-varying covariates in a subdistribution hazard model results in the loss of the ability to estimate the cumulative incidence function (CIF) or the effect of covariates on the CIF. Furthermore, the definition of the risk set for the subdistribution hazard function can make defining internal time-varying covariates difficult or impossible. We conducted a review of the use of time-varying covariates in subdistribution hazard models in articles published in the medical literature in 2015 and in the first 5 months of 2019. Seven percent of articles published included a time-varying covariate. Several inappropriately described a time-varying covariate as having an association with the risk of the outcome.

Meta-analysis of clinical trials with competing time-to-event endpoints.

Recommendations for the analysis of competing risks in the context of randomized clinical trials are well established. Meta-analysis of individual patient data (IPD) is the gold standard for synthesizing evidence for clinical interpretation based on multiple studies. Surprisingly, no formal guidelines have been yet proposed to conduct an IPD meta-analysis with competing risk endpoints. To fill this gap, this work details (i) how to handle the heterogeneity between trials via a stratified regression model for competing risks and (ii) that the usual metrics of inconsistency to assess heterogeneity can readily be employed. Our proposal is illustrated by the re-analysis of a recently published meta-analysis in nasopharyngeal carcinoma, aiming at quantifying the benefit of the addition of chemotherapy to radiotherapy on each competing endpoint.