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Biomedical subjects

C B Begg

Publications and source records attributed to C B Begg.

At least 55 records · Page 3Linked to original sources
PubMed1990

High-dose ifosfamide with mesna uroprotection: a phase I study.

Phase II trials of ifosfamide have been performed with standard doses of 5 to 8 g/m2/course. In this phase I study, 29 patients were treated with a 4-day continuous infusion ifosfamide to determine the maximum-tolerated dose and the nonhematologic dose-limiting toxicity. Autologous bone marrow support was to have been used for the subsequent dose level if granulocytes were more than 500/microL for more than 14 days in two of two to five patients at a given dose level. Doses were escalated from 8 to 18 g/m2 ifosfamide. Mesna was given at an equivalent dose by continuous infusion for 5 days. At the 18 g/m2 dose level, dose-limiting renal insufficiency and a median of 11 days (range, 8 to 18 days) of granulocytopenia (less than 500/microL) were observed. Thus, autologous bone marrow reinfusion ws not used. The duration of myelosuppression, the frequency and severity of mucositis, and renal tubular acidosis were all dose-dependent. Mild to moderate CNS toxicity also appeared to be related to dose; however, severe CNS toxicity (transient confusion, hallucinations, and somnolence) was observed sporadically at both low- and high-dose levels. Transient hematuria (greater than 50 red blood cells [RBCs]/high power field) occurred once but did not affect treatment. There were nine responses (two complete) in 27 heavily pretreated assessable patients including seven responses in 20 patients with advanced refractory sarcoma. Ifosfamide with mesna uroprotection can undergo considerable dose escalation over the usual prescribed doses before nonhematologic dose-limiting toxicity is encountered. Ifosfamide has broad cytotoxicity against solid tumors and may prove to be an important addition to high-dose combination chemotherapy regimens.

Blood↗
PubMed1989

Publication bias and dissemination of clinical research.

Publication bias is a widely recognized phenomenon that occurs because of the influence of study results on the chances of publication. Usually, studies with positive results are more likely to be published than studies with negative results, which leads to a preponderance of false-positive results in the literature. Empiric studies have demonstrated that the induced bias is large and can have a serious impact on meta-analyses, in which data from several studies are aggregated, as well as on informal reviews. The problem is deeply embedded in current research practice, which encourages demonstration of statistical significance to "prove" theories, and one of its causes is the pressure to publish extensively that is an integral part of the competition for academic promotion. Serious efforts to reduce this problem will involve restructuring the process by which study results are disseminated, changing editorial policies, and altering the style and methods of statistical analysis.

Attitude of Health Personnel↗
PubMed1989

Diverse prognosis in metastatic breast cancer: who should be offered alternative initial therapies?

In an attempt to clarify appropriate treatment options for women with stage IV breast cancer, we studied the survival experience of a large dataset of patients treated on Cancer and Leukemia Group B (CALGB) protocols. The study, restricted to women who had had no prior chemotherapy for metastatic disease, demonstrated a surprisingly poor prognosis, with an estimated median survival of 1.6 years and only 26% alive at 3 years. Analysis of prognostic factors permitted the identification of subsets with even shorter survival, such as women with estrogen receptor negative tumor in more than one metastatic site and prior adjuvant chemotherapy. We feel that an evaluation of intensive investigational treatment approaches, such as trials using autologous bone marrow transplantation, is justified for most stage IV breast cancer patients, in view of their poor prognosis.

Biomarkers, Tumor↗
PubMed1988

The association of patients' socioeconomic characteristics with the length of hospital stay and hospital charges within diagnosis-related groups.

To determine whether the hospital stays are longer and charges within a given diagnosis-related group (DRG) are higher for poor patients, we examined patterns of care for patients hospitalized at the Brigham and Women's Hospital for connective-tissue disorders (DRGs 240 and 241) from 1981 to 1985. The socioeconomic characteristics of 402 patients were determined through interviews, and the severity of their illness was measured by means of a standard scale of function--the Instrumental Activities of Daily Living (IADL) scale. After excluding outliers and adjusting for DRG, we found that hospital stays were significantly longer for subgroups of patients of lower socioeconomic status, whether this was defined by occupation, education, or income (P less than 0.05 for all three). Patients of low socioeconomic status also had higher total hospital charges, although the differences were not statistically significant. The differences between patients of low socioeconomic status and those of high socioeconomic status were as great as 25 percent for length of stay and 16 percent for charges. These trends persisted after we adjusted for patients' age and sex, the severity of illness, the year of discharge, the doctor's specialty, whether the patient had a regular doctor, and whether the patient lived alone. Our results suggest that for at least some conditions, hospital care for poor patients entails longer stays and probably requires the use of more resources.

Activities of Daily Living↗
PubMed1988

Assessment of radiologic tests: control of bias and other design considerations.

The assessment of new radiologic tests can be seriously hampered by the presence of systematic bias. Biases can arise from incomplete verification of the sample population; omission of uninterpretable tests; absence of a definitive reference test; extraneous factors affecting interpretation; and extrapolation factors including variations in test efficacy among patients, hospitals, and the radiologists who interpret the tests. The authors review these biases that affect the results of efficacy studies and provide guidelines to avoid these problems.

Evaluation Studies as Topic↗
PubMed1988

High peripheral blast count in adult acute myelogenous leukemia is a primary risk factor for CNS leukemia.

The lengthening remission duration achievable in acute myelogenous leukemia (AML) places patients at risks for CNS leukemic relapse. We reviewed the data on two Eastern Cooperative Oncology Group (ECOG) trials in acute nonlymphocytic leukemia to determine the incidence of CNS leukemia (CNSL). The incidence of CNSL was 5% (30 of 569 patients) overall, and 3% (ten of 331) in patients in complete remission (CR). A number of factors were evaluated for association with increased risk of CNSL. Men more frequently developed CNSL than women at a three to one ratio, and median presenting WBC counts were higher in affected than unaffected patients (44,200/microL v 17,000/microL, P = .01). The low incidence of CNSL in AML supports the view that CNS prophylaxis is unnecessary. However, because 68% of patients (13 of 19) who developed CNSL early in the course of disease had presenting WBC counts greater than 40,000/microL, screening lumbar punctures should be routinely obtained during induction therapy in patients presenting with high circulating blast cell counts.

Brain Neoplasms↗
PubMed1987

State of the art in comparative cancer clinical trials.

In order to investigate the current state of the art in clinical cancer research, a survey of comparative cancer clinical trials was conducted using a MEDLINE literature search of the 6-month interval from July to December of 1985. Data were obtained primarily from the published abstracts. The major observations from the study are as follows. First, trials in cancer research are published in an extraordinarily wide range of journals covering most of the major medical specialties in addition to the many cancer specialty journals. Second, randomization is now used quite extensively. It is the predominant method of control in chemotherapy trials and in trials reported in cancer journals. However, its use is much less common in other specialties, especially surgery, so efforts to popularize randomization in these specialties would be beneficial. Third, sample sizes are highly variable, and the median sample size (96 patients) is too small to reliably detect and evaluate moderate treatment advances. Finally, our survey reveals that published trials show an inordinately large proportion of breakthroughs in treatment compared with the generally accepted view that only slow progress is being made in developing effective cancer treatments. Our view is that this result reflects the strong tendency to publish only studies with positive results. This hypothesis is supported by the fact that in nonrandom trials there tend to be more positive conclusions and an absence of a strong association between conclusions and sample size.

Clinical Trials as Topic↗
PubMed1987

Biases in the assessment of diagnostic tests.

Diagnostic tests are traditionally characterized by simple measures of efficacy such as the sensitivity and the specificity. These measures, though widely recognized and easy to understand, are subject to definitional arbitrariness. Moreover, studies constructed to estimate the sensitivity and specificity are susceptible to a variety of biases. In this paper the various potential problems are described with reference to examples from the diagnostic literature. These difficulties have implications for the design of diagnostic test evaluations, and the choice of suitable measures of test efficacy.

Clinical Laboratory Techniques↗
PubMed1987

The impact of treatment allocation procedures on nominal significance levels and bias.

Complete randomization, the simplest method for allocating treatments to patients in clinical trials, can serve as a basis for inferential procedures using standard permutation tests, because the method ensures that each sequence of allocations is equally likely. No other method of allocation possesses this property. However, many clinical trials employ allocation methods that force balance of covariates across treatment groups. With these methods, some allocation sequences are impossible or highly unlikely so that standard permutation tests are technically invalidated. In this article we investigate whether standard permutation tests for binary outcomes are likely to yield distorted nominal p values in practical applications of these alternative allocation methods. A sample of completed trials conducted by the Eastern Cooperative Oncology Group serves as a basis on which to construct simulations. Our results indicate that nominal p values can be conservative, but are not likely to be severely distorted if the analysis is stratified by important covariates used as allocation prompts. Moreover the inherent conservativeness of exact methods due to discreteness tends to dominate any additional conservativeness due to nonrandom designs. In addition, we investigate the relationship of treatment allocation methods with bias in estimates from a logistic model when important covariates are unknown. This bias is the same for all asymptotically balanced allocation methods and is significant but not disastrous.

Analysis of Variance↗
PubMed1987

Evaluation of efficient designs for observational epidemiologic studies.

Recent research in the design of observational epidemiologic studies has been focused on determining which design is most efficient for controlling a potential confounding factor in the analysis of the disease-exposure relationship. Typically, only two candidate designs have been considered, the matched design and the random sample design. These are merely two of an infinite variety of potential designs in which the distributions of the confounder in the comparison groups and the ratio of group sample sizes are arbitrarily chosen. Only in special cases will either of the standard designs be the most efficient or "optimal" design. We construct optimal designs by minimizing the variance of the desired estimate of effect with respect to the controllable design parameters. Construction of an optimal design depends on unknown parameters, so that in practice only an approximately optimal design, perhaps constructed sequentially, is possible. We evaluate the potential usefulness of optimal designs by identifying circumstances in which an optimal design results in large efficiency gains relative to both the matched and random sample designs. We find that there can be substantial efficiency gains in follow-up studies when both the exposure and confounder are strong risk factors. Practical issues in the implementation of these designs are discussed.

Epidemiologic Methods↗