Evolution of Resistance to Targeted Anti-Cancer Therapies during Continuous and Pulsed Administration Strategies

The discovery of small molecules targeted to specific oncogenic pathways has revolutionized anti-cancer therapy. However, such therapy often fails due to the evolution of acquired resistance. One long-standing question in clinical cancer research is the identification of optimum therapeutic administration strategies so that the risk of resistance is minimized. In this paper, we investigate optimal drug dosing schedules to prevent, or at least delay, the emergence of resistance. We design and analyze a stochastic mathematical model describing the evolutionary dynamics of a tumor cell population during therapy. We consider drug resistance emerging due to a single (epi)genetic alteration and calculate the probability of resistance arising during specific dosing strategies. We then optimize treatment protocols such that the risk of resistance is minimal while considering drug toxicity and side effects as constraints. Our methodology can be used to identify optimum drug administration schedules to avoid resistance conferred by one (epi)genetic alteration for any cancer and treatment type

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]

Do women ⩾50 years of age need as much screening as women <50 years after they have had negative screening results?

To assess the adequacy of a routine screening to identify cervical intraepithelial neoplasia 2 or worse (CIN2+) in women over 50 years of age, a retrospective cohort was set in six Italian organised population-based screening programmes. In all, 287 330 women (1 714 550 person-years of observation, 1110 cases) screened at age 25–64, with at least two cytological screening tests, the first negative, were followed from their first negative smear until a biopsy proven CIN2+ lesion or their last negative smear. For women aged 25–49 and 50–64 years, crude and age-standardised detection rate (DR), cumulative risk (CR), adjusted hazard risk for number of previous negative screens, probability of false-positive CIN2+ after two or more smear tests were calculated. Detection rate is significantly lower over 50 years of age. Multivariable analysis shows a significant protective effect from four screening episodes (DR=0.70, 95% CI: 0.51–0.97); the effect of age ⩾50 is 0.29 (95% CI: 0.24–0.35). The CR of CIN2+ is at least eightfold higher in women <50 (CR=2.06, 95% CI: 1.88–2.23) after one previous negative test than in women ⩾50 years with four screens (CR=0.23, 95% CI: 0.00–0.46). Over 50 years of age, after four tests at least three false-positive cases are diagnosed for every true positive. Benefits arising from cytological screening is uncertain in well-screened older women

Comparison of 1- and 2-year screening intervals for women undergoing screening mammography

We compared the long-term impact of 1- and 2-year screening mammography intervals using prognostic, screening, and outcome information for women aged 50–74 years obtained from the Screening Mammography Program of British Columbia in two time periods, prior to 1997 (policy of annual mammography) and after 1997 (biennial mammography). Survival was estimated for both periods using a prognostic model and the expected rate of interval and screen-detected cancers. The likelihood of a screen-detected cancer with annual screening was 2.32 per thousand screens and with biennial screening was 3.32 per thousand screens. The prognostic profile of screen-detected cancers was better than that of interval cancers. Among both screen-detected and interval cancers, the prognostic profiles with annual and biennial screening were similar. The estimated breast cancer-specific survival rates for women undergoing annual and biennial screening mammography were 95.2 and 94.6% at 5 years, and 90.4 and 89.2% at 10 years, respectively. Annual compared to biennial mammography was associated with a 1.2% increase in the estimated 10-year breast cancer-specific survival for women aged 50–74 years, diagnosed with invasive breast cancer after screening programme attendance

The increase in cancer prevalence and hospital burden in Western Australia, 1992-2011

Purpose - To describe cancer prevalence and hospital service utilization by prevalent cancer patients in Western Australia from 1992 to 2011. Methods - This study was a population-based cohort study using the Western Australia (WA) Cancer Registry (1982 to 2011) as the source of incident cancer cases. These data were linked to mortality (1982 to 2011) and hospital morbidity (1998 to 2011) records via the WA Data Linkage System to ascertain complete and limited-duration prevalence and cancer-related hospitalizations over time. Prevalence rates were calculated using estimated residential population data from the Australian Bureau of Statistics. Results - In 2011, one in every 27 people living in WA had been diagnosed with cancer at some time in their lifetime, and one in 68 had been diagnosed within the previous five years. Between 1992 and 2011, complete cancer prevalence in Western Australia increased by a magnitude of 2.5-fold. Forty-five and 44% of the increase in complete cancer prevalence in males and females between 1992 and 2011 can be attributed to prostate and breast cancer, respectively. The absolute number of cancer-related bed days increased 81 and 74% in males and females, respectively, diagnosed within one year, between 1998 and 2011. Conclusions - The prevalence of cancer and the burden it places on hospitals continues to rise, demanding ongoing efforts to prevent cancer through modifiable risk factors and better, more efficient use of health resources. Steps should to be taken to understand and address overdiagnosis and overtreatmen