Oncological Safety of Oncoplastic Level II Mammoplasties After Neoadjuvant Chemotherapy for Large Breast Cancers: A Matched-Cohort Analysis.

BACKGROUND: Oncoplastic surgery (OPS) has extended the indications for breast-conserving surgery (BCS). Its role in patients with large breast cancers treated with neoadjuvant chemotherapy (NAC) is unclear. This study evaluated the oncological safety of OPS for tumors with partial response after NAC. METHODS: A consecutive series of 65 patients who underwent OPS (study group) after NAC for large breast cancer from January 2004 to July 2018 was compared with 130 matched patients treated by NAC, followed by standard BCS in 65 cases and mastectomy in 65 cases (two case-controlled groups). RESULTS: The mean initial radiological tumor size was 46 mm. Residual pathological tumor size was 22 mm in the OPS cohort, 19 mm in the standard BCS cohort, and 31 mm in the mastectomy cohort (p > 0.05). The mean follow-up was 59 months in the study cohort. Five-year local recurrence rates were 0%, 0%, and 10.5% (0-22%) for the OPS, BCS, and mastectomy cohorts, respectively, while 5-year regional recurrence rates were 4.1% (0-11.1%), 0, and 19.4% (0-35.2%, p > 0.05), respectively. Five-year overall survival was 85.3% for the OPS cohort, 94.1% for the standard BCS cohort (p = 0.194), and 79.9% for the mastectomy cohort (p = 0.165). CONCLUSIONS: OPS is safe after NAC for large breast cancers, and provides excellent local control, identical to that of tumors with a better response, treated by standard BCS. After NAC, OPS can be a valuable treatment option for tumors that did not shrink optimally and would not be suitable for standard BCS.

Identification and validation of DOCK4 as a potential biomarker for risk of bone metastasis development in patients with early breast cancer.

Skeletal metastasis occurs in around 75% of advanced breast cancers, with the disease incurable once cancer cells disseminate to bone, but there remains an unmet need for biomarkers to identify patients at high risk of bone recurrence. This study aimed to identify such a biomarker and to assess its utility in predicting response to adjuvant zoledronic acid (zoledronate). We used quantitative proteomics (stable isotope labelling by amino acids in cell culture-mass spectrometry; SILAC-MS) to compare protein expression in a bone-homing variant (BM1) of the human breast cancer cell line MDA-MB-231 with parental non-bone-homing cells to identify novel biomarkers for risk of subsequent bone metastasis in early breast cancer. SILAC-MS showed that dedicator of cytokinesis protein 4 (DOCK4) was upregulated in bone-homing BM1 cells, confirmed by western blotting. BM1 cells also had enhanced invasive ability compared with parental cells, which could be reduced by DOCK4-shRNA. In a training tissue microarray (TMA) comprising 345 patients with early breast cancer, immunohistochemistry followed by Cox regression revealed that high DOCK4 expression correlated with histological grade (p = 0.004) but not oestrogen receptor status (p = 0.19) or lymph node involvement (p = 0.15). A clinical validation TMA used tissue samples and the clinical database from the large AZURE adjuvant study (n = 689). Adjusted Cox regression analyses showed that high DOCK4 expression in the control arm (no zoledronate) was significantly prognostic for first recurrence in bone (HR 2.13, 95%CI 1.06-4.30, p = 0.034). No corresponding association was found in patients who received zoledronate (HR 0.812, 95%CI 0.176-3.76, p = 0.790), suggesting that treatment with zoledronate may counteract the higher risk for bone relapse from high DOCK4-expressing tumours. High DOCK4 expression was not associated with metastasis to non-skeletal sites when these were assessed collectively. In conclusion, high DOCK4 in early breast cancer is significantly associated with aggressive disease and with future bone metastasis and is a potentially useful biomarker for subsequent bone metastasis risk. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Long-term Results After Oncoplastic Surgery for Breast Cancer: A 10-year Follow-up.

OBJECTIVE: The aim of this study was to evaluate the long-term oncologic outcome after oncoplastic surgery (OPS). BACKGROUND: OPS combines wide tumor excision with reduction mammoplasty techniques thus extending breast conserving surgery to large tumors that might else be proposed a mastectomy. Little data are available about the oncologic results for breast conserving surgery of these larger tumors. METHODS: From January 2004 until March 2016, a total of 350 oncoplastic breast reductions were prospectively entered into a database. Patients were included if their breast reshaping included a reduction mammoplasty with skin excision (Level 2 oncoplastic techniques). RESULTS: Histologic subtypes were: invasive ductal carcinoma in 219 cases (62.6%), ductal carcinoma in situ (DCIS) in 88 cases (25.1%), and invasive lobular carcinoma in 43 (12.3%) cases. Seventy-three of the invasive cancers (27.9%) received neoadjuvant chemotherapy. The mean resection weight was 177 grams. The mean pathological tumor size was 26 mm (range 0-180 mm) and varied from 23 mm (4-180 mm) for invasive cancers to 32 mm (0-100 mm) for DCIS. Specimen margins were involved in 12.6% of the cases; 10.5% of invasive ductal, 14.7% of DCIS, and 20.9% of invasive lobular. The overall breast conservation rate was 92% and varied from 87.4% for DCIS to 93.5% for the invasive cancers. Thirty-one patients (8.9%) developed one or more postoperative complications, inducing a delay in postoperative treatments in 4.6% of patients. The median follow up was 55 months. The cumulative 5-year incidences for local, regional, and distant recurrences were 2.2%, 1.1%, and 12.4%, respectively. CONCLUSIONS: Oncoplastic breast reductions allow wide resections with free margins and can be used for large cancers as an alternative to mastectomy.

Expression of Programmed Death Ligand 1 in Penile Cancer is of Prognostic Value and Associated with HPV Status.

PURPOSE: PD-L1 (programmed death ligand 1) inhibits T-cell function and prevents tumor eradication. This is facilitated by PD-L1 positive tumor cells and PD-L1 positive immune cells, and can be prevented by anti-PD-1 (programmed death 1)/PD-L1 immunotherapy. In advanced penile cancer there is a need for new therapeutic strategies. We investigated PD-L1 expression in penile cancers and compared PD-L1 expression with disease specific survival, lymph node metastases at diagnosis and high risk HPV status in a large patient cohort. MATERIALS AND METHODS: A total of 213 primary tumors were immunohistochemically stained for PD-L1 and scored for tumor (percentage), stroma (binary) and PD-L1 positive tumor infiltrating macrophages. Additionally, PD-L1 positive tumors were scored for expression pattern, that is diffuse or predominantly present at the tumor-stroma margin. RESULTS: Staining was successful in 200 tumors, of which 75% were high risk HPV negative. Median followup was 62 months. Of 200 tumors 96 (48%) were PD-L1 positive (scored 1% or greater), of which 59 (62%) had a marginal expression pattern and 79 (82%) were high risk HPV negative (p = 0.03). Compared to PD-L1 negative tumors, the PD-L1 expression patterns had different prognostic values in the whole cohort as well as in the high risk HPV negative subgroup. On multivariable analyses a marginal expression pattern was associated with absent lymph node metastases (OR 0.4) while diffuse expression was associated with poor survival (HR 2.58). These results were more prominent in the high risk HPV negative subgroup (OR 0.25, HR 3.92). CONCLUSIONS: PD-L1 was expressed in 48% of penile carcinomas and mainly in high risk HPV negative tumors. The pattern of expression was a prognostic factor as marginal expression was associated with absent lymph node metastases and diffuse expression was associated with poor survival.

Frequent inactivating mutations of STAG2 in bladder cancer are associated with low tumour grade and stage and inversely related to chromosomal copy number changes.

Inactivating mutations of STAG2 have been reported at low frequency in several cancers. In glioblastoma, the function of STAG2 has been related to maintenance of euploidy via its role in the cohesin complex. In a screen of a large series of bladder tumours and cell lines, we found inactivating mutations (nonsense, frameshift and splicing) in 67 of 307 tumours (21.8%) and 6 of 47 cell lines. Thirteen missense mutations of unknown significance were also identified. Inactivating mutation was associated with low tumour stage (P = 0.001) and low grade (P = 0.0002). There was also a relationship with female patient gender (P = 0.042). Examination of copy number profiles revealed an inverse relationship of mutation with both fraction of genome altered and whole chromosome copy number changes. Immunohistochemistry showed that in the majority of cases with inactivating mutations, STAG2 protein expression was absent. Strikingly, we identified a relatively large subset of tumours (12%) with areas of both positive and negative immunoreactivity, in only four of which a potentially function-altering mutation was detected. Regions of differential expression were contiguous and showed similar morphological phenotype in all cases. Microdissected positive and negative areas from one tumour showed an inactivating mutation to be present only in the negative area, suggesting intra-tumoral sub-clonal genomic evolution. Our findings indicate that loss of STAG2 function plays a more important role in non-invasive than that in muscle-invasive bladder cancer and suggest that cohesin complex-independent functions are likely to be important in these cases.

Using common variants to indicate cancer genes.

The catalogue of tumour-specific somatic mutations (SMs) is growing rapidly owing to the advent of next-generation sequencing. Identifying those mutations responsible for the development and progression of the disease, so-called driver mutations, will increase our understanding of carcinogenesis and provide candidates for targeted therapeutics. The phenotypic consequence(s) of driver mutations cause them to be selected for within the tumour environment, such that many approaches aimed at distinguishing drivers are based on finding significantly somatically mutated genes. Currently, these methods are designed to analyse, or be specifically applied to, nonsynonymous mutations: those that alter an encoded protein. However, growing evidence suggests the involvement of noncoding transcripts in carcinogenesis, mutations in which may also be disease-driving. We wished to test the hypothesis that common DNA variation rates within humans can be used as a baseline from which to score the rate of SMs, irrespective of coding capacity. We preliminarily tested this by applying it to a dataset of 159,498 SMs and using the results to rank genes. This resulted in significant enrichment of known cancer genes, indicating that the approach has merit. As additional data from cancer sequencing studies are made publicly available, this approach can be refined and applied to specific cancer subtypes. We named this preliminary version of our approach PRISMAD (polymorphism rates indicate somatic mutations as drivers) and have made it publicly accessible, with scripts, via a link at www.precancer.leeds.ac.uk/software-and-datasets.

FGFR3 expression in primary invasive bladder cancers and matched lymph node metastases.

PURPOSE: FGFR3 is considered a good therapeutic target for bladder cancer. However, to our knowledge it is unknown whether the FGFR3 status of primary tumors is a surrogate for related metastases, which must be targeted by FGFR targeted systemic therapies. We assessed FGFR3 protein expression in primary bladder tumors and matched nodal metastases. MATERIALS AND METHODS: We examined matched primary tumor and nodal metastases from 150 patients with bladder cancer clinically staged as N0M0. Four samples per patient were incorporated into a tissue microarray and FGFR3 expression was assessed by immunohistochemistry. FGFR3 expression was tested for an association with categorical clinical data using the Fisher exact test, and with overall and recurrence-free survival by Kaplan-Meier analysis. RESULTS: Duplicate spots from primary tumors and lymph node metastases were highly concordant (OR 8.6 and 16.7, respectively, each p <0.001). Overall FGFR protein expression levels did not differ between primary and metastatic lesions (p = 0.78). Up-regulated expression was recorded in 53 of 106 evaluable primary tumor spots and 56 matched metastases. Concordance of FGFR3 expression levels in 79 matched primary tumor and metastasis specimens was high (OR 8.45, p <0.001). In 15 and 12 patients expression was up-regulated in only metastasis and in only the primary tumor, respectively. Overall and recurrence-free survival was not related to FGFR3 expression. CONCLUSIONS: FGFR3 expression in matched primary and metastasized bladder cancer specimens showed good but not absolute concordance. Thus, in most patients primary tumor FGFR3 status can guide the selection of FGFR targeted therapy.

The prognostic significance of tumour-stroma ratio in endometrial carcinoma.

BACKGROUND: High tumour stromal content has been found to predict adverse clinical outcome in a range of epithelial tumours. The aim of this study was to assess the prognostic significance of tumour-stroma ratio (TSR) in endometrial adenocarcinomas and investigate its relationship with other clinicopathological parameters. METHODS: Clinicopathological and 5-year follow-up data were obtained for a retrospective series of endometrial adenocarcinoma patients (n=400). TSR was measured using a morphometric approach (point counting) on digitised histologic hysterectomy specimens. Inter-observer agreement was determined using Cohen's Kappa statistic. TSR cut-offs were optimised using log-rank functions and prognostic significance of TSR on overall survival (OS) and disease-free survival (DFS) were determined using Cox Proportional Hazards regression analysis and Kaplan-Meier curves generated. Associations of TSR with other clinicopathological parameters were determined using non-parametric tests followed by Holm-Bonferroni correction for multiple comparisons. RESULTS: TSR as a continuous variable associated with worse OS (P=0.034) in univariable Cox-regression analysis. Using the optimal cut-off TSR value of 1.3, TSR-high (i.e. low stroma) was associated with worse OS (HR=2.51; 95% CI=1.22-5.12; P=0.021) and DFS (HR=2.19; 95% CI=1.15-4.17; P=0.017) in univariable analysis. However, TSR did not have independent prognostic significance in multivariable analysis, when adjusted for known prognostic variables. A highly significant association was found between TSR and tumour grade (P<0.001) and lymphovascular space invasion (P<0.001), both of which had independent prognostic significance in this study population. CONCLUSIONS: Low tumour stromal content associates with both poor outcome and with other adverse prognostic indicators in endometrial cancer, although it is not independently prognostic. These findings contrast with studies on many--although not all--cancers and suggest that the biology of tumour-stroma interactions may differ amongst cancer types.

Diethylstilboestrol (1 mg) in the management of castration-resistant prostate cancer.

OBJECTIVE: To investigate the efficacy of diethylstilboestrol (DES) in patients with advanced prostate cancer refractory to androgen suppression. METHODS: This retrospective study comprises 194 patients with prostate cancer treated with DES (1 mg daily) between 1976 and 2010. Study outcome parameters included demographic data, tumour characteristics, treatment history, prostate-specific antigen (PSA) responses, radiologic studies, adverse events and overall survival. RESULTS: At initiation of oestrogen therapy the mean patient age was 69 years (range: 48-89) and the median PSA was 96 ng/ml (range: 1.9-9,500). The median duration of prior prostate cancer treatment was 29 months (range: 1-365). DES was the second-line treatment in 58 patients and the third/fourth-line therapy in 136 men. A formal (≥50%) PSA response was observed in 95 patients (48.9%) and the median time to progression (TTP) was 250 days (95% CI, 180-360) for this group. An additional 62 patients (31.9%) had a partial PSA response with a median TTP of 150 days (95% CI, 92-180). Thirty-seven patients (19.1%) did not have a PSA response and the median TTP was 90 days (95% CI, 90-97). The median overall survival from the start of oestrogen therapy for the entire cohort was 576 days (95% CI, 482-690). The median overall survival of patients who had a formal (≥50%), partial (<50%) and no PSA response was 756 (95% CI, 670-1,429), 428 (95% CI, 340-630) and 329 (95% CI, 287-510) days, respectively. Thirty-nine patients (20.1%) were still alive at the end of the study. No treatment-related deaths occurred. CONCLUSIONS: In the age of chemotherapy this study highlights the efficacy of oestrogen therapy in castration-refractory prostate cancer. The optimal point in the therapeutic pathway at which DES should be prescribed remains to be established.

Experimental designs for detecting synergy and antagonism between two drugs in a pre-clinical study.

The identification of synergistic interactions between combinations of drugs is an important area within drug discovery and development. Pre-clinically, large numbers of screening studies to identify synergistic pairs of compounds can often be ran, necessitating efficient and robust experimental designs. We consider experimental designs for detecting interaction between two drugs in a pre-clinical in vitro assay in the presence of uncertainty of the monotherapy response. The monotherapies are assumed to follow the Hill equation with common lower and upper asymptotes, and a common variance. The optimality criterion used is the variance of the interaction parameter. We focus on ray designs and investigate two algorithms for selecting the optimum set of dose combinations. The first is a forward algorithm in which design points are added sequentially. This is found to give useful solutions in simple cases but can lack robustness when knowledge about the monotherapy parameters is insufficient. The second algorithm is a more pragmatic approach where the design points are constrained to be distributed log-normally along the rays and monotherapy doses. We find that the pragmatic algorithm is more stable than the forward algorithm, and even when the forward algorithm has converged, the pragmatic algorithm can still out-perform it. Practically, we find that good designs for detecting an interaction have equal numbers of points on monotherapies and combination therapies, with those points typically placed in positions where a 50% response is expected. More uncertainty in monotherapy parameters leads to an optimal design with design points that are more spread out.

The potential utility of geminin as a predictive biomarker in breast cancer.

Compared with other markers of cell proliferation, geminin is unique being expressed selectively during the proliferative phase of the cell cycle, specifically S, G2 and early mitosis, disappearing completely at the metaphase-anaphase transition. We aimed to compare the prognostic significance of geminin to that of Ki67, a proliferation marker which has been investigated in many breast cancer studies. Breast cancer tissue microarrays containing 368 tumours were stained using anti-geminin and Ki67 antibodies. Labelling index (LI) was calculated for geminin, and the percentage of positive cancer nuclei was determined for Ki67. A receiver operation characteristics analysis was used to determine the optimum cut-off value for geminin (LI ≥ 2), and for Ki67, a score of ≥14 % was considered as positive for survival analysis. Geminin expression correlated positively with Ki67 expression (r = 0.686, p = 0.001). Survival analysis showed only geminin, and not Ki67-positive patients to have poor (breast cancer-specific survival) BCSS [HR 2.85 (1.53-5.32)] and (disease-free survival) DFS [HR 2.63 (1.47-4.71)]. On univariate analysis, along with known clinicopathological variables, both Ki67 and geminin LI were found to be significant predictors of BCSS and DFS. On multivariate analysis, only tumour size, nodal status and adjuvant hormonal therapy were found to be independent predictors for both BCSS and DFS, while geminin positivity (LI ≥ 2 %) was found to be an independent predictor for BCSS [HR 2.27 (1.01-5.06); p = 0.04]. In comparison with Ki67, a more established proliferation marker, geminin expression was a better predictor of adverse outcome in this cohort of breast cancers. Selective expression of geminin during the proliferative phase of the cell cycle and its nuclear specificity increase its potential to be used as an alternative marker of proliferation in breast cancer patients.

MiR-26b is down-regulated in carcinoma-associated fibroblasts from ER-positive breast cancers leading to enhanced cell migration and invasion.

Carcinoma-associated fibroblasts (CAFs) influence the behaviour of cancer cells but the roles of microRNAs in this interaction are unknown. We report microRNAs that are differentially expressed between breast normal fibroblasts and CAFs of oestrogen receptor-positive cancers, and explore the influences of one of these, miR-26b, on breast cancer biology. We identified differentially expressed microRNAs by expression profiling of clinical samples and a tissue culture model: miR-26b was the most highly deregulated microRNA. Using qPCR, miR-26b was confirmed as down-regulated in fibroblasts from 15 of 18 further breast cancers. Next, we examined whether manipulation of miR-26b expression changed breast fibroblast behaviour. Reduced miR-26b expression caused fibroblast migration and invasion to increase by up to three-fold in scratch-closure and trans-well assays. Furthermore, in co-culture with MCF7 breast cancer epithelial cells, fibroblasts with reduced miR-26b expression enhanced both MCF7 migration in trans-well assays and MCF7 invasion from three-dimensional spheroids by up to five-fold. Mass spectrometry was used to identify expression changes associated with the reduction of miR-26b expression in fibroblasts. Pathway analyses of differentially expressed proteins revealed that glycolysis/TCA cycle and cytoskeletal regulation by Rho GTPases are downstream of miR-26b. In addition, three novel miR-26b targets were identified (TNKS1BP1, CPSF7, COL12A1) and the expression of each in cancer stroma was shown to be significantly associated with breast cancer recurrence. MiR-26b in breast CAFs is a potent regulator of cancer behaviour in oestrogen receptor-positive cancers, and we have identified key genes and molecular pathways that act downstream of miR-26b in CAFs.

Identification of stage-specific breast markers using quantitative proteomics.

Matched healthy and diseased tissues from breast cancer patients were analyzed by quantitative proteomics. By comparing proteomic profiles of fibroadenoma (benign tumors, three patients), DCIS (noninvasive cancer, three patients), and invasive ductal carcinoma (four patients), we identified protein alterations that correlated with breast cancer progression. Three 8-plex iTRAQ experiments generated an average of 826 protein identifications, of which 402 were common. After excluding those originating from blood, 59 proteins were significantly changed in tumor compared with normal tissues, with the majority associated with invasive carcinomas. Bioinformatics analysis identified relationships between proteins in this subset including roles in redox regulation, lipid transport, protein folding, and proteasomal degradation, with a substantial number increased in expression due to Myc oncogene activation. Three target proteins, cofilin-1 and p23 (increased in invasive carcinoma) and membrane copper amine oxidase 3 (decreased in invasive carcinoma), were subjected to further validation. All three were observed in phenotype-specific breast cancer cell lines, normal (nontransformed) breast cell lines, and primary breast epithelial cells by Western blotting, but only cofilin-1 and p23 were detected by multiple reaction monitoring mass spectrometry analysis. All three proteins were detected by both analytical approaches in matched tissue biopsies emulating the response observed with proteomics analysis. Tissue microarray analysis (361 patients) indicated cofilin-1 staining positively correlating with tumor grade and p23 staining with ER positive status; both therefore merit further investigation as potential biomarkers.

Investigation of the robustness of two models for assessing synergy in pre-clinical drug combination studies.

Pre-clinical studies may be used to screen for synergistic combinations of drugs. The types of in vitro assays used for this purpose will depend upon the disease area of interest. In oncology, one frequently used study measures cell line viability: cells placed into wells on a plate are treated with doses of two compounds, and cell viability is assessed from an optical density measurement corrected for blank well values. These measurements are often transformed and analysed as cell survival relative to untreated wells. The monotherapies are assumed to follow the Hill equation with lower and upper asymptotes at 0 and 1, respectively. Additionally, a common variance about the dose-response curve may be assumed. In this paper, we consider two models for incorporating synergy parameters. We investigate the effect of different models of biological variation on the assessment of synergy from both of these models. We show that estimates of the synergy parameters appear to be robust, even when estimates of the other model parameters are biased. Using untransformed measurements provides better coverage of the 95% confidence intervals for the synergy parameters than using transformed measurements, and the requirement to fit the upper asymptote does not cause difficulties. Assuming homoscedastic variances appears to be robust. The added complexity of determining and fitting an appropriate heteroscedastic model does not seem to be justified.

A Comparative Evaluation of Mediastinal Nodal SUVmax and Derived Ratios from 18F-FDG PET/CT Imaging to Predict Nodal Metastases in Non-Small Cell Lung Cancer.

18F-FDG positron emission tomography with computed tomography (PET/CT) is a standard imaging modality for the nodal staging of non-small cell lung cancer (NSCLC). To improve the accuracy of pre-operative staging, we compare the staging accuracy of mediastinal lymph node (LN) standard uptake values (SUV) with four derived SUV ratios based on the SUV values of primary tumours (TR), the mediastinal blood pool (MR), liver (LR), and nodal size (SR). In 2015-2017, 53 patients (29 women and 24 men, mean age 67.4 years, range 53-87) receiving surgical resection have pre-operative evidence of mediastinal nodal involvement (cN2). Among these, 114 mediastinal nodes are resected and available for correlative PET/CT analysis. cN2 status accuracy is low, with only 32.5% of the cN2 cases confirmed pathologically. Using receiver operating characteristic (ROC) curve analyses, a SUVmax of N2 LN performs well in predicting the presence of N2 disease (AUC, 0.822). Based on the respective selected thresholds for each ROC curve, normalisation of LN SUVmax to that for mediastinum, liver and tumour improved sensitivities of LN SUVmax from 68% to 81.1-89.2% while maintaining acceptable specificity (68-70.1%). In conclusion, normalised SUV ratios (particularly LR) improve current pre-operative staging performance in detecting mediastinal nodal involvement.

A novel Phase I/IIa design for early phase oncology studies and its application in the evaluation of MK-0752 in pancreatic cancer.

The Cancer Research UK study CR0720-11 is a trial to determine the tolerability and effect on survival of using two agents in combination in patients with advanced pancreatic cancer. In particular, the trial is designed first to identify the most suitable combination of doses of the two agents in terms of the incidence of dose-limiting toxicities. Then, the survival of all patients who have received that dose combination in the study so far, together with additional patients assigned to that dose combination to ensure that the total number is sufficient, will be analysed. If the survival outcomes show promise, then a definitive randomised study of that dose combination will be recommended. The first two patients in the trial will be treated with the lowest doses of each agent in combination. An adaptive Bayesian procedure based only on monotonicity constraints concerning the risks of toxicity at different dose levels will then be used to suggest dose combinations for subsequent patients. The survival analysis will concern only patients who received the chosen dose combination, and will compare observed mortality with that expected from an exponential model based on the known survival rates associated with current treatment. In this paper, the Bayesian dose-finding procedure is described and illustrated, and its properties are evaluated through simulation. Computation of the appropriate sample size for the survival investigation is also discussed.

A bivariate Bayesian dose-finding procedure applied to a seamless phase I/II trial in rheumatoid arthritis.

We describe a dose escalation procedure for a combined phase I/II clinical trial. The procedure is based on a Bayesian model for the joint distribution of the occurrence of a dose limiting event and of some indicator of efficacy (both considered binary variables), making no assumptions other than monotonicity. Thus, the chances of each outcome are assumed to be non-decreasing in dose level. We applied the procedure to the design of a placebo-controlled, sequential trial in rheumatoid arthritis, in each stage of which patients were randomized between placebo and all dose levels that currently appeared safe and non-futile. On the basis of data from a pilot study, we constructed five different scenarios for the dose-response relationships under which we simulated the trial and assessed the performance of the procedure. The new design appears to have satisfactory operating characteristics and can be adapted to the requirements of a range of trial situations.

Bayesian procedures for phase I/II clinical trials investigating the safety and efficacy of drug combinations.

Many formal statistical procedures for phase I dose-finding studies have been proposed. Most concern a single novel agent available at a number of doses and administered to subjects participating in a single treatment period and returning a single binary indicator of toxicity. Such a structure is common when evaluating cytotoxic drugs for cancer. This paper concerns studies of combinations of two agents, both available at several doses. Subjects participate in one treatment period and provide two binary responses: one an indicator of benefit and the other of harm. The word 'benefit' is used loosely here: the response might be an early indicator of physiological change which, if induced in patients, is of potential therapeutic value. The context need not be oncology, but might be any study intended to meet both the phase I aim of establishing which doses are safe and the phase II goal of exploring potential therapeutic activity. A Bayesian approach is used based on an assumption of monotonicity in the relationship between the strength of the dose-combination and the distribution of the bivariate outcome. Special cases are described, and the procedure is evaluated using simulation. The parameters that define the model have immediate and simple interpretation. Graphical representations of the posterior opinions about model parameters are shown, and these can be used to inform the discussions of the trial safety committee.

Estimation strategies for reacting to the identification of an association between the genome and adverse drug reactions.

The availability of high-resolution genetic profiling raises the possibility, during the course of a drug development program, of discovering a subset of patients at particular risk of an adverse drug reaction who might be excluded from subsequent randomization into studies and identified as unsuitable for post-licensing use. Such methods depend on the estimation of the risk of adverse drug reactions for patients with differing genetic profiles followed by an assessment of the risks and benefits of their exposure to the drug. In this paper we explore the performance of a number alternative statistical methods for the estimation of risk in terms of the success of the subsequent exclusion rules. The approaches were evaluated using a single-nucleotide polymorphism dataset concerning HIV patients at risk of hypersensitivity to the drug abacavir. Overall we found that a method based on LASSO performed better than the alternatives that we studied, which included a decision-theoretic Bayesian approach, and that its performance suggested suitability for its prospective implementation.

A Bayesian dose-finding procedure for phase I clinical trials based only on the assumption of monotonicity.

Despite an enormous and growing statistical literature, formal procedures for dose-finding are only slowly being implemented in phase I clinical trials. Even in oncology and other life-threatening conditions in which a balance between efficacy and toxicity has to be struck, model-based approaches, such as the Continual Reassessment Method, have not been universally adopted. Two related concerns have limited the adoption of the new methods. One relates to doubts about the appropriateness of models assumed to link the risk of toxicity to dose, and the other is the difficulty of communicating the nature of the process to clinical investigators responsible for early phase studies. In this paper, we adopt a new Bayesian approach involving a simple model assuming only monotonicity in the dose-toxicity relationship. The parameters that define the model have immediate and simple interpretation. The approach can be applied automatically, and we present a simulation investigation of its properties when it is. More importantly, it can be used in a transparent fashion as one element in the expert consideration of what dose to administer to the next patient or group of patients. The procedure serves to summarize the opinions and the data concerning risks of a binary characterization of toxicity which can then be considered, together with additional and less tidy trial information, by the clinicians responsible for making decisions on the allocation of doses. Graphical displays of these opinions can be used to ease communication with investigators.