Evaluation of the contribution of randomised cancer clinical trials evaluating agents without documented single-agent activity.

BACKGROUND: With the development of targeted agents, the approach to combination cancer therapy has evolved to focus on identifying ways in which pathway inhibition by one agent may enhance the activity of other agents. In theory, this implies that under this new paradigm, agents are no longer required to show single-agent activity, as the pathway inhibited by the targeted agent may only have a therapeutic effect when given with other agents. This raises the question of the extent to which anticancer agents without single-agent activity can contribute to effective combination regimens. PATIENTS AND METHODS: We reviewed outcomes of randomised phase 2 combination trials sponsored by the National Cancer Institute Cancer Therapy Evaluation Program that were activated in 2008 to 2017 and noted the single-agent activity of the experimental agents. RESULTS: Fifty-three trials were identified, and 50 had available results: 7 (14%), 15 (30%) and 28 (56%) had experimental agents with single-agent activity classified as active, inactive and indeterminate, respectively. Thirteen per cent (95% CI=1.7% to 40.5%) of trials evaluating inactive agents and 11.6% (95% CI=3.9% to 25.1%) of trials evaluating agents without known single-agent activity (pooled inactive and indeterminate) were positive, compared with 42.9% (95% CI=9.9% to 81.6%) for agents with single-agent activity. CONCLUSIONS: Incorporating agents without documented single-agent activity into treatment regimens is unlikely to produce meaningful improvements in activity unless there is compelling biological rationale. This finding has important implications for the prioritisation of anticancer agents for combination testing, and for the allocation of clinical trial resources.

Interim monitoring for non-inferiority trials: minimizing patient exposure to inferior therapies.

The goal of a non-inferiority randomized trial is to demonstrate that an experimental treatment is not unacceptably worse than a standard treatment. The experimental treatment is known to have less toxicity or other quality-of-life benefits when compared with the standard treatment, so that a small decrement in efficacy would be acceptable. Interim monitoring of randomized trials is used to stop trials early if the conclusions of the trial become definitive early. In the context of a non-inferiority trial, of special interest is stopping a trial early when the experimental treatment is inferior to the standard treatment. Methods for performing interim monitoring of non-inferiority trials are reviewed for their ability to minimize patient exposure to inferior experimental treatments. Examples of trials from the literature are discussed along with a computer simulation of a simple non-inferiority monitoring rule. Interim monitoring for non-inferiority trials is shown to substantially reduce the exposure of patients to inferior therapies when, in fact, the experimental treatment is inferior to the standard treatment. Interim monitoring rules typically used in superiority trials may be sub-optimal for non-inferiority trials, and may unnecessarily expose patients to inferior therapies. Examples of trials with inferior experimental arms and trials with sub-optimal monitoring rules are given. Appropriate interim monitoring of non-inferiority trials can reduce the exposure of patients to inferior therapies when the experimental treatment is inferior to the standard treatment.

Assessing treatment efficacy in the subset of responders in a randomized clinical trial.

BACKGROUND: Durability of response is a clinically relevant dimension of the treatment effect in randomized clinical trials; it is often measured by comparing among the responders the duration of response between the treatment arms. However, since the comparison groups are defined by response (a post-randomization event), it is subject to analysis-by-responder bias, especially if the proportion of responders differs between the arms. METHODS: Two simple methods are developed that use tumor shrinkage measurements in order to lessen analysis-by-responder bias by generating more comparable patient subsets in the control and experimental arms of the trial. These subsets are then used to estimate between-arm differences in response duration. In the subtraction method, responding patients with the least tumor shrinkage in the treatment arm with more responders are removed from the patient subset for that arm. In the addition method, non-responding patients with the most tumor shrinkage in the treatment arm with fewer responders are added to the patient subset for that arm. In both methods, the numbers of patients subtracted or added are such that the proportion of patients in the modified patient subset is the same as the proportion of responders in the other treatment arm. RESULTS: The methods are demonstrated on a hypothetical dataset where they are shown to eliminate analysis-by-responder bias, and on two published analyses of randomized trials that compared the duration of response between the treatment arms. CONCLUSIONS: The proposed methods can lessen the analysis-by-responder bias. These methods to compare duration of response between treatment arms may provide a useful exploratory analysis to measure treatment efficacy among responders.

Statistical controversies in clinical research: assessing pathologic complete response as a trial-level surrogate end point for early-stage breast cancer.

BACKGROUND: A trial-level surrogate end point for a randomized clinical trial may allow assessment of the relative benefits of the treatment to be performed at an earlier time point and potentially with a smaller sample size. However, determining whether an end point is a reliable trial-level surrogate based on results of previous trials is not straightforward. The question of trial-level surrogacy is easily confused with the question of individual-level surrogacy, and this confusion can lead to controversy. A recent example concerns the evaluation of pathologic complete response (pCR) as a surrogate for event-free survival (EFS) and overall survival (OS) in early-stage breast cancer. MATERIALS AND METHODS: The differences between individual-level surrogacy (i.e. for patients receiving a specific treatment, the surrogate end point predicts the definitive end point) and trial-level surrogacy (the results of the trial for the surrogate end point predict the results of the trial for the definitive end point) are discussed. Trial-level data used in two previous meta-analyses evaluating pCR as a trial-level surrogate for EFS and OS were re-analyzed using methods that appropriately account for the variability in pCR rates as well as the variability in the hazard ratios for EFS and OS. RESULTS: There is no evidence that pCR is a trial-level surrogate for EFS or OS, nor is there evidence that pCR could be used reliably to screen out nonpromising agents from further drug development. CONCLUSIONS: At present, neoadjuvant RCTs should continue to follow patients to observe EFS and OS to assess clinical benefit, and they should be designed with sufficient sample size to reliably assess EFS. However, one cannot rule out the possibility that future meta-analyses involving more trials and in which the patient population or class of treatments is restricted could suggest the validity of pCR as a trial-level surrogate for EFS or OS in some focused settings.

Evaluation of chemoresponse assays as predictive markers.

BACKGROUND: A chemoresponse assay that can be used to predict which patients will respond to which drugs would be useful in directing treatment. Two new analytic methods to assess the predictive ability of a chemoresponse assay have been proposed by Tian et al. METHODS: Three examples in which a hypothetical assay has no predictive ability are considered to evaluate the properties of the proposed analytic methods. RESULTS: For these specific examples, the proposed methods incorrectly suggest that the assay is predictive. CONCLUSIONS: The examples presented here demonstrate that it can be challenging to evaluate the predictive value of a chemoresponse assay.

Assessing causal relationships between treatments and clinical outcomes: always read the fine print.

Changes in clinical practice should be driven by relevant and reliable evidence. Hence, adoption of a new therapy requires demonstrating that it provides (causes) benefit. Such evidence is generally obtained from intent-to-treat analyses of randomized clinical trials (RCTs). In this paper, we review other approaches to assessing the causal relationship between treatments and outcomes: (1) inference from non-randomized (observational) studies, (2) analysis of randomized studies where patients received treatments other than those to which they were randomized and (3) analysis of studies where the outcome of interest is sometimes unobservable because of a competing event (competing risks). We conclude that for the practice-changing demonstration of a favorable benefit-to-risk ratio, the gold standard is the intent-to-treat analysis of RCTs. At the same time, we illustrate how careful application of special statistical methods for assessment of treatment-outcome causation can be instrumental in complementing existing randomized evidence and guiding design of future research.

Identifying pre-post chemotherapy differences in gene expression in breast tumours: a statistical method appropriate for this aim.

Although widely used for the analysis of gene expression microarray data, cluster analysis may not be the most appropriate statistical technique for some study aims. We demonstrate this by considering a previous analysis of microarray data obtained on breast tumour specimens, many of which were paired specimens from the same patient before and after chemotherapy. Reanalysing the data using statistical methods that appropriately utilise the paired differences for identification of differentially expressed genes, we find 17 genes that we can confidently identify as more expressed after chemotherapy than before. These findings were not reported by the original investigators who analysed the data using cluster analysis techniques.

A prospective randomized phase II trial of GM-CSF priming to prevent topotecan-induced neutropenia in chemotherapy-naive patients with malignant melanoma or renal cell carcinoma.

We conducted a phase II randomized trial of recombinant granculocyte-macrophage colony-stimulating factor (GM-CSF) administered before topotecan chemotherapy to determine whether it could prevent myelosuppression and to determine the antitumor activity of this topoisomerase I inhibitor in 53 patients with metastatic malignant melanoma and renal cell cancer. All patients received GM-CSF after topotecan at a dose of 250 microg/m(2) daily for at least 8 days. Patients randomly assigned to receive GM-CSF priming were treated with GM-CSF at 250 microg/m(2) twice daily for 5 days before treatment. Twenty-five patients were randomly assigned to receive GM-CSF priming and 28 to receive topotecan without priming. The primary analysis was restricted to the protective effects seen during the first cycle of therapy. Grade 4 neutropenia occurred in 8 of 23 patients (35%) and grade 3 neutropenia in 5 of 23 patients (22%) randomized to GM-CSF priming, whereas 18 of 26 (69%) and 5 of 26 (19%) patients experienced grade 4 or 3 neutropenia, respectively, without GM-CSF priming (P =.0074). The mean duration of neutropenia was reduced by GM-CSF priming: grade 3 neutropenia from 5.2 +/- 0.7 to 2.8 +/- 0.7 days (P =.0232) and grade 4 neutropenia from 2.7 +/- 0.6 to 1.1 +/- 0.4 days (P = 0.0332). The protective effects of GM-CSF extended to the second cycle of treatment. The incidence of febrile neutropenia was also reduced. Chemotherapy-induced anemia and thrombocytopenia were similar in both groups. One partial response was seen in a patient with melanoma, and one patient with renal cell cancer had complete regression of pulmonary metastases and was rendered disease-free by nephrectomy. (Blood. 2001;97:1942-1946)

Clinical trial designs for cytostatic agents: are new approaches needed?

Preclinical data suggest that some new anticancer agents directed at novel targets demonstrate tumor growth inhibition but not tumor shrinkage. Such cytostatic agents may offer clinical benefits for patients in the absence of tumor shrinkage. In addition, lower doses of some of these agents may be just as effective as higher doses, implying that toxicity may not be an ideal end point for dose finding. Because of these factors, the sequence and design of traditional phase I, II, and III trials used for cytotoxic agents (which typically shrink tumors and in a dose-dependent manner) may not be appropriate for cytostatic agents. This article discusses options for modifying trial designs to accommodate cytostatic agents. Examples are given where these options have been tried or are currently being tried. Recommendations given for choosing among the trial designs depend on what is known preclinically about the agents (eg, does one have a validated and reproducible biologic end point that can be used to guide a dose escalation?), what is known about the patient population being studied (eg, does one have a well-documented historical progression-free survival rate at 1 year for comparison with the experience of the new agent?), and the numbers of agents and patients available for participation in trials. Planned and ongoing trials will test the utility of some of these new approaches.

Data monitoring committees and interim monitoring guidelines.

Most large randomized clinical trials have a data monitoring committee that periodically examines efficacy and safety results. A typical data monitoring committee meets every 6 months, but the interim monitoring guidelines for many trials specify formal analyses that are years apart. In this article we argue that study protocols should include monitoring guidelines with formal looks at each data monitoring committee meeting. Such guidelines are shown to reduce the average duration of a trial with negligible effect on power and estimation bias. Some of the common statistical monitoring guidelines require extreme evidence to stop a trial early and do not distinguish between stopping a trial during active accrual and follow-up stages. We propose practical solutions for these issues.

Analyzing health surveys for cancer-related objectives.

Large-scale health surveys conducted by government agencies record information on a large number of health-related variables. We review the use of these data for performing analyses that address cancer-related objectives. After describing the conduct of a large-scale health survey (the third National Health and Nutrition Examination Survey [NHANES III]), we discuss some of the issues involved in analyzing data collected in such a survey. In particular, the use of sample weights in the analysis and the importance of accounting for the complex survey design when estimating standard errors are discussed. Six applications are then presented that involve the following: 1) estimating demographic factors associated with snuff use, 2) estimating the association of type of health insurance with the probability of receiving a digital rectal examination, 3) estimating the association of body iron stores with the probability of later developing cancer, 4) estimating the changing rates of mammography screening in the United States between 1987 and 1992, 5) evaluating smoking and alcohol consumption as risk factors for digestive cancer by use of a population-based, case-control study, and 6) evaluating a randomized community-intervention experiment to encourage smoking cessation. These applications use data from the National Health Interview Survey, the NHANES I Epidemiologic Followup Study, the 1986 National Mortality Followback Survey, and the Community Intervention Trial for Smoking Cessation. The availability of public-use data files is discussed for surveys sponsored by the U.S. government that collect health-related information. We demonstrate that statistical methods and computer software are available for analyzing public-use data files of surveys to address different types of cancer-related objectives.

Abrogation of the hematological and biological activities of the interleukin-3/granulocyte-macrophage colony-stimulating factor fusion protein PIXY321 by neutralizing anti-PIXY321 antibodies in cancer patients receiving high-dose carboplatin.

This dose-escalation study was performed to evaluate the hematologic activity, biological effects, immunogenicity, and toxicity of PIXY321 (an interleukin-3/granulocyte-macrophage colony-stimulating factor fusion protein) administered after high-dose carboplatin (CBDCA) treatment. Patients with advanced cancers received CBDCA at 800 mg/m2 intravenously on day 0 of repeated 28-day cycles. In part A of the study, patients were treated with CBDCA alone during cycle 1 and then received PIXY321 on days 1 through 18 of cycle 2 and later cycles. In part B, patients received 18 days of PIXY321 beginning on day 1 of all CBDCA cycles, including cycle 1. PIXY321 was administered subcutaneously in 2 divided doses. Total doses of 135, 250, 500, 750, and 1,000 micrograms/m2/d were administered to successive cohorts of 3 to 6 patients in part A. In part B, patient groups received PIXY321 doses of 750, 1,000, and 1,250 micrograms/m2/d. The hematologic effects of PIXY321 were assessed in the first 2 cycles of therapy. Anti-PIXY321 antibody formation was assessed by enzyme-linked immunosorbent assay (ELISA) and neutralization assay. Of the 49 patients enrolled, 31 were fully evaluable for hematologic efficacy. When comparing the first B cycle (cycle B-1; with PIXY321) with the first A cycle (cycle A-1; without PIXY321), the fusion protein had no significant effect on platelet nadirs or duration of platelets less than 20,000/microL but was able to speed the time of recovery of platelet counts to 100,000/microL (15 v 20 days; P =.01). Significant improvements in neutrophil nadir and duration of ANC less than 500 were observed in cycles A-2 and B-1 (with PIXY321) as compared with cycle A-1 (without PIXY321). Initial PIXY321 prophylaxis (cycle A-2 and cycle B-1), enhanced the recovery of ANC to greater than 1,500/microL by an average of at least 8 days as compared with cycle A-1 (without PIXY321; P

Predictive margins with survey data.

In the analysis of covariance, the display of adjusted treatment means allows one to compare mean (treatment) group outcomes controlling for different covariate distributions in the groups. Predictive margins are a generalization of adjusted treatment means to nonlinear models. The predictive margin for group r represents the average predicted response if everyone in the sample had been in group r. This paper discusses the use of predictive margins with complex survey data, where an important consideration is the choice of covariate distribution used to standardize the predictive margin. It is suggested that the textbook formula for the standard error of an adjusted treatment mean from the analysis of covariance may be inappropriate for applications involving survey data. Applications are given using data from the 1992 National Health Interview Survey (NHIS) and the Epidemiologic Followup Study to the first National Health and Nutrition Examination Survey (NHANES I).

Role of independent data-monitoring committees in randomized clinical trials sponsored by the National Cancer Institute.

PURPOSE: To describe the rationale for independent data monitoring committees (DMCs) for National Cancer Institute (NCI)-sponsored phase III cooperative group clinical trials. DESIGN: We review the necessity for interim monitoring of outcome data during the course of randomized clinical trials and summarize the reasons for establishing DMCs with requisite expertise and with appropriate independence from study investigators. RESULTS: The important components of the policy for cooperative group DMCs are described with a focus on the makeup of these bodies and on the complementary roles of study committee leadership and DMCs in protecting patient safety during the conduct of randomized clinical trials. CONCLUSION: The cooperative group DMCs that are independent of the study committees and that have the requisite expertise to examine accumulating data and to base decisions on monitoring guidelines that are specified in advance by the study committee provide a body able to protect patient safety, to protect the integrity of the clinical experiments on which patients have consented to participate, and to assure the public that conflicts of interest do not compromise either patient safety or trial integrity.

Lower molar and incisor displacement associated with mandibular remodeling.

The purpose of this study was to quantify the amount of alveolar modeling at the apices of the mandibular incisor and first molar specifically associated with appositional and resorptive changes on the lower border of the mandible during growth and treatment. Cephalometric data from superimpositions on anterior cranial base, mandibular implants of the Björk type, and anatomical "best fit" of mandibular border structures were integrated using a recently developed strategy, which is described. Data were available at annual intervals between 8.5 and 15.5 years for a previously described sample of approximately 30 children with implants. The average magnitudes of the changes at the root apices of the mandibular first molar and central incisor associated with modeling/remodeling of the mandibular border and symphysis were unexpectedly small. At the molar apex, mean values approximated zero in both anteroposterior and vertical directions. At the incisor apex, mean values approximated zero in the anteroposterior direction and averaged less than 0.15 mm/year in the vertical direction. Standard deviations were roughly equal for the molar and the incisor in both the anteroposterior and vertical directions. Dental displacement associated with surface modeling plays a smaller role in final tooth position in the mandible than in the maxilla. It may also be reasonably inferred that anatomical best-fit superimpositions made in the absence of implants give a more complete picture of hard tissue turnover in the mandible than they do in the maxilla.

Time-to-event analysis of longitudinal follow-up of a survey: choice of the time-scale.

Following individuals sampled in a large-scale health survey for the development of diseases and/or death offers the opportunity to assess the prognostic significance of various risk factors. The proportional hazards regression model, which allows for the control of covariates, is frequently used for the analysis of such data. The authors discuss the appropriate time-scale for such regression models, and they recommend that age rather than time since the baseline survey (time-on-study) be used. Additionally, with age as the time-scale, control for calendar-period and/or birth cohort effects can be achieved by stratifying the model on birth cohort. Because, as discussed by the authors, many published analyses have used regression models with time-on-study as the time-scale, it is important to assess the magnitude of the error incurred from this type of incorrect modeling. The authors provide simple conditions for when incorrect use of time-on-study as the time-scale will nevertheless yield approximately unbiased proportional hazards regression coefficients. Examples are given using data from the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Followup Study. Additional issues concerning the analysis of longitudinal follow-up of survey data are briefly discussed.

Data monitoring committees and problems of lower-than-expected accrual or events rates.

Data monitoring committees for randomized clinical trials must frequently decide what action, if any, is required for trials whose accrual has been slower than expected, or whose event rates have been less than expected. We discuss in this article some of the practical issues concerning modifying or closing such trials, including what data and analyses could be helpful to the data monitoring committee in their deliberations.

Apical root resorption in orthodontically treated adults.

This study analyzed the relationship in orthodontically treated adults between upper central incisor displacement measured on lateral cephalograms and apical root resorption measured on anterior periapical x-ray films. A multiple linear regression examined incisor displacements in four directions (retraction, advancement, intrusion, and extrusion) as independent variables, attempting to account for observed differences in the dependent variable, resorption. Mean apical resorption was 1.36 mm (sd +/- 1.46, n = 73). Mean horizontal displacement of the apex was -0.83 mm (sd +/- 1.74, n = 67); mean vertical displacement was 0.19 mm (sd +/- 1.48, n = 67). The regression coefficients for the intercept and for retraction were highly significant; those for extrusion, intrusion, and advancement were not. At the 95% confidence level, an average of 0.99 mm (se = +/- 0.34) of resorption was implied in the absence of root displacement and an average of 0.49 mm (se = +/- 0.14) of resorption was implied per millimeter of retraction. R2 for all four directional displacement variables (DDVs) taken together was only 0.20, which implied that only a relatively small portion of the observed apical resorption could be accounted for by tooth displacement alone. In a secondary set of univariate analyses, the associations between apical resorption and each of 14 additional treatment-related variables were examined. Only Gender, Elapsed Time, and Total Apical Displacement displayed statistically significant associations with apical resorption. Additional multiple regressions were then performed in which the data for each of these three statistically significant variables were considered separately, with the data for the four directional displacement variables. The addition of information on Elapsed Time or Total Apical Displacement did not explain a significant additional portion of the variability in apical resorption. On the other hand, the addition of information on Gender to the information on the four directional displacement variables yielded an R2 value of 0.35, which indicated that these variables taken together could account for approximately a third of the observed variability in apical resorption in this sample.