Chronic Leukemias

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66325/1/j.1365-4362.1982.tb03146.x.pd

Detection of Melanoma Nodal Metastases; Differences in Detection Between Elderly and Younger Patients Do Not Affect Survival

Background. Melanoma lymph nodes metastases may be detected by patients or by physicians. Understanding the outcomes of self-detection or physician detection is essential for the design of follow-up studies. We evaluated the role of the method of detection in nodal disease in the prognosis of melanoma patients who underwent therapeutic lymph node dissection (TLND). Materials and Methods. All melanoma patients with palpable lymph nodes were included in a prospective database (n = 98), and the method of detection was recorded. Detection of lymph node metastases compared with pathological findings in the TLND was assessed by multivariate logistic regression. Disease-free survival (DFS) and disease-specific survival (DSS) were assessed by univariate and multivariate Cox proportional hazard analysis. Results. Nodal metastases were detected by physicians in 45% and by patients in 55% (P <0.001). Age was significantly associated with method of detection. Patients 60 years (odds ratio [OR] 0.3; P = 0.007). However, this was not associated with prognostic findings in TLND, number of positive nodes, tumor size, or extranodal spread. Method of detection or age at the time of nodal metastases was not significantly associated with 2-year DFS or DSS. Conclusions. 45% of all lymph node metastases in stage I-II melanoma patients are physician detected. Younger patients detect their own lymph node metastases significantly more often than elderly patients. However, neither the method of detection nor age correlates with DSS. More frequent follow-up would not alter DFS and DSS significantly

Optimizing Combination Therapies with Existing and Future CML Drugs

Small-molecule inhibitors imatinib, dasatinib and nilotinib have been developed to treat Chromic Myeloid Leukemia (CML). The existence of a triple-cross-resistant mutation, T315I, has been a challenging problem, which can be overcome by finding new inhibitors. Many new compounds active against T315I mutants are now at different stages of development. In this paper we develop an algorithm which can weigh different combination treatment protocols according to their cross-resistance properties, and find the protocols with the highest probability of treatment success. This algorithm also takes into account drug toxicity by minimizing the number of drugs used, and their concentration. Although our methodology is based on a stochastic model of CML microevolution, the algorithm itself does not require measurements of any parameters (such as mutation rates, or division/death rates of cells), and can be used by medical professionals without a mathematical background. For illustration, we apply this algorithm to the mutation data obtained in [1], [2]