Search PubMed⌕ Search

PubMed · 348088

ARA-C analogs.

Abstract

Ara-C, a phase-specific antitumor agent, is rapidly deactivated by the enzyme cytidine deaminase. A prolongation of the biological activity of ara-C can be achieved either by the concomitant use of a cytidine deaminase inhibitor or by the development of ara-C derivatives with increased resistance to deamination and a longer half-life in serum. Among such derivatives are cyclocytidine (cyclo-C), anhydro-ara-5-fluorocytidine (AAFC) and the N4-acyl-derivatives. AAFC has been recently shown to be active in human leukemias and in solid tumors of the digestive tract. The tolerance to AAFC is sufficient for clinical use, and AAFC does not produce parotid pains and hypotension, characteristic side effects of cyclo-C. The main toxicity consists of myelodepression, nausea and vomiting. The schedule dependence of AAFC is far less pronounced than for ara-C, so that a weekly application by rapid i.v. injection of 30-40 mg/kg (1,200-1,500 mg/m2) reaches the level of activity with acceptable toxicity. AAFC seems to be as active as ara-C in acute leukemias and is probably active too in malignant lymphomas. In a large phase II trial of the EORTC on selected solid tumor types, AAFC showed a significant activity in GI tract adenocarcinomas with 2 responses/3 evaluable in pancreas, 7/14 in stomach and 2/32 in colorectal tumors (4/30). Hints of activity were also detected in breast cancer (1/17) and anaplastic small cell carcinoma of the lung (1/9). No responses were obtained in 27 patients with epidermoid carcinoma of the lung. These results confirm that ara-C, or newer ara-C analogs, are potentially active in various solid tumor types, and suggest that an extensive further clinical study of such new derivatives is warranted.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

P Alberto. 1978. ARA-C analogs.. https://doi.org/10.1159/000401475

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

On the exact interval estimation for the difference in paired areas under the ROC curves.

An important measure for comparison of accuracy between two diagnostic procedures is the difference in paired areas under the receiver operating characteristic (ROC) curves. Non-parametric and maximum likelihood methods have been proposed for interval estimation for the difference in paired areas under ROC curves. However, these two methods are asymptotic procedures and their performance in finite sample sizes has not been thoroughly investigated. We propose to use the concept of generalized pivotal quantities (GPQs) to construct an exact confidence interval for the difference in paired areas under ROC curves. A simulation study is conducted to empirically investigate the probability coverage and expected length of the three methods for various combinations of sample sizes, values of the area under the ROC curve and correlations. Simulation results demonstrate that the exact confidence interval based on the concept of GPQs provides not only sufficient probability coverage but also reasonable expected length. Numerical examples using published data sets illustrate the proposed method.

Clinical Trials as Topic↗

An efficient test for the analysis of dichotomized variables when the reliability is known.

A difference in an outcome variable between the treatment groups in a trial does not necessarily mean that there is a difference in the number of patients who experience relevant improvement on that variable. When the relevant improvement corresponds with an outcome or change in outcome that exceeds a certain threshold, the outcome variable can be dichotomized. A responder is a patient whose outcome exceeds the threshold. Comparisons can be made between the number of responders in the two treatment groups using logistic regression, or some other method to evaluate binary outcomes. An important disadvantage of this approach is the loss of power. In general, it is more efficient to test the difference between the mean values. We developed a statistical test that compares response rates for a dichotomized variable. It requires that an estimate of the reliability of the outcome variable is available. Simulations showed that the test was valid and robust over a wide range of distributions and sample sizes. The power was greater than the power of a chi(2) test, which would enable substantial reduction in the sample size.

Clinical Trials as Topic↗

Sample size determination for logistic regression revisited.

There is no consensus on the approach to compute the power and sample size with logistic regression. Some authors use the likelihood ratio test; some use the test on proportions; some suggest various approximations to handle the multivariate case. We advocate the use of the Wald test since the Z-score is routinely used for statistical significance testing of regression coefficients. The null-variance formula became popular from early studies, which contradicts modern software, which utilizes the method of maximum likelihood estimation (MLE), when the variance of the MLE is estimated at the MLE, not at the null. We derive general Wald-based power and sample size formulas for logistic regression and then apply them to binary exposure and confounder to obtain a closed-form expression. These formulas are applied to minimize the total sample size in a case-control study to achieve a given power by optimizing the ratio of controls to cases. Approximately, the optimal number of controls to cases is equal to the square root of the alternative odds ratio. Our sample size and power calculations can be carried out online at www.dartmouth.edu/ approximately eugened.

Clinical Trials as Topic↗