Two-stage estimation to adjust for treatment switching in randomised trials: A simulation study investigating the use of inverse probability weighting instead of re-censoring

Background Treatment switching is common in randomised trials of oncology treatments, with control group patients switching onto the experimental treatment during follow-up. This distorts an intention-to-treat comparison of the treatments under investigation. Two-stage estimation (TSE) can be used to estimate counterfactual survival times for patients who switch treatments – that is, survival times that would have been observed in the absence of switching. However, when switchers do not die during the study, counterfactual censoring times are estimated, inducing informative censoring. Re-censoring is usually applied alongside TSE to resolve this problem, but results in lost longer-term information – a major concern if the objective is to estimate long-term treatment effects, as is usually the case in health technology assessment. Inverse probability of censoring weights (IPCW) represents an alternative technique for addressing informative censoring but has not before been combined with TSE. We aim to determine whether combining TSE with IPCW (TSEipcw) represents a valid alternative to re-censoring. Methods We conducted a simulation study to compare TSEipcw to TSE with and without re-censoring. We simulated 48 scenarios where control group patients could switch onto the experimental treatment, with switching affected by prognosis. We investigated various switching proportions, treatment effects, survival function shapes, disease severities and switcher prognoses. We assessed the alternative TSE applications according to their estimation of control group restricted mean survival (RMST) that would have been observed in the absence of switching up to the end of trial follow-up. Results TSEipcw performed well when its weights had a low coefficient of variation, but performed poorly when the coefficient of variation was high. Re-censored analyses usually under-estimated control group RMST, whereas non-re-censored analyses usually produced over-estimates, with bias more serious when the treatment effect was high. In scenarios where TSEipcw performed well, it produced low bias that was often between the two extremes associated with the re-censoring and non-recensoring options. Conclusions Treatment switching adjustment analyses using TSE should be conducted with re-censoring, without re-censoring, and with IPCW to explore the sensitivity in results to these application options. This should allow analysts and decision-makers to better interpret the results of adjustment analyses

When to wait for more evidence?: real options analysis in proton therapy.

Purpose. Trends suggest that cancer spending growth will accelerate. One method for controlling costs is to examine whether the benefits of new technologies are worth the extra costs. However, especially new and emerging technologies are often more costly, while limited clinical evidence of superiority is available. In that situation it is often unclear whether to adopt the new technology now, with the risk of investing in a suboptimal therapy, or to wait for more evidence, with the risk of withholding patients their optimal treatment. This trade-off is especially difficult when it is costly to reverse the decision to adopt a technology, as is the case for proton therapy. Real options analysis, a technique originating from financial economics, assists in making this trade-off. Methods. We examined whether to adopt proton therapy, as compared to stereotactic body radiotherapy, in the treatment of inoperable stage I non-small cell lung cancer. Three options are available: adopt without further research; adopt and undertake a trial; or delay adoption and undertake a trial. The decision depends on the expected net gain of each option, calculated by subtracting its total costs from its expected benefits. Results. In The Netherlands, adopt and trial was found to be the preferred option, with an optimal sample size of 200 patients. Increase of treatment costs abroad and costs of reversal altered the preferred option. Conclusion. We have shown that real options analysis provides a transparent method of weighing the costs and benefits of adopting and/or further researching new and expensive technologies. The Oncologist 2011;16:1752-176

Assessing methods for dealing with treatment crossover in clinical trials: A follow-up simulation study

Background: Treatment switching commonly occurs in clinical trials of novel interventions, particularly in the advanced or metastatic cancer setting, which causes important problems for health technology assessment. Previous research has demonstrated which adjustment methods are suitable in specific scenarios, but scenarios considered have been limited. Objectives: We aimed to assess statistical approaches for adjusting survival estimates in the presence of treatment switching in order to determine which methods are most appropriate in a new range of realistic scenarios, building upon previous research. In particular we consider smaller sample sizes, reduced switching proportions, increased levels of censoring, and alternative data generating models. Methods: We conducted a simulation study to assess the bias, mean squared error and coverage associated with alternative switching adjustment methods across a wide range of realistic scenarios. Results: Our results generally supported those found in previous research, but the novel scenarios considered meant that we could make conclusions based upon a more robust evidence base. Simple methods such as censoring or excluding patients that switch again resulted in high levels of bias. More complex randomisation-based methods (e.g. Rank Preserving Structural Failure Time Models (RPSFTM)) were unbiased when the “common treatment effect” held. Observational-based methods (e.g. inverse probability of censoring weights (IPCW)) coped better with time-dependent treatment effects but are heavily data reliant, and generally led to higher levels of bias in our simulations. Novel “two stage” methods produced relatively low bias across all simulated scenarios. All methods generally produced higher bias when the simulated sample size was smaller and when the censoring proportion was higher. All methods generally produced lower bias when switching proportions were lower. We find that the size of the treatment effect in terms of an acceleration factor has an important bearing on the levels of bias associated with the adjustment methods. Conclusions: Randomisation-based methods can accurately adjust for treatment switching when the treatment effect received by patients that switch is the same as that received by patients randomised to the experimental group. When this is not the case observational-based methods or simple twostage methods should be considered, although the IPCW is prone to substantial bias when the proportion of patients that switch is greater than approximately 90%. Simple methods such as censoring or excluding patients that switch should not be used

Digital Quantum Simulation with Rydberg Atoms

We discuss in detail the implementation of an open-system quantum simulator with Rydberg states of neutral atoms held in an optical lattice. Our scheme allows one to realize both coherent as well as dissipative dynamics of complex spin models involving many-body interactions and constraints. The central building block of the simulation scheme is constituted by a mesoscopic Rydberg gate that permits the entanglement of several atoms in an efficient, robust and quick protocol. In addition, optical pumping on ancillary atoms provides the dissipative ingredient for engineering the coupling between the system and a tailored environment. As an illustration, we discuss how the simulator enables the simulation of coherent evolution of quantum spin models such as the two-dimensional Heisenberg model and Kitaev's toric code, which involves four-body spin interactions. We moreover show that in principle also the simulation of lattice fermions can be achieved. As an example for controlled dissipative dynamics, we discuss ground state cooling of frustration-free spin Hamiltonians.Comment: submitted to special issue "Quantum Information with Neutral Particles" of "Quantum Information Processing

Nonstable K-Theory for graph algebras

We compute the monoid V (LK(E)) of isomorphism classes of finitely generated projective modules over certain graph algebras LK(E), and we show that this monoid satisfies the refinement property and separative cancellation. We also show that there is a natural isomorphism between the lattice of graded ideals of LK(E) and the lattice of order-ideals of V (LK(E)). When K is the field C of complex numbers, the algebra LC(E) is a dense subalgebra of the graph C -algebra C (E), and we show that the inclusion map induces an isomorphism between the corresponding monoids. As a consequence, the graph C*-algebra of any row-finite graph turns out to satisfy the stable weak cancellation propert

Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events

The $B^0$-$\bar B^0$ oscillation frequency has been measured with a sample of 23 million \B\bar B pairs collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we select events in which both B mesons decay semileptonically and use the charge of the leptons to identify the flavor of each B meson. A simultaneous fit to the decay time difference distributions for opposite- and same-sign dilepton events gives $\Delta m_d = 0.493 \pm 0.012{(stat)}\pm 0.009{(syst)}$ ps$^{-1}$.Comment: 7 pages, 1 figure, submitted to Physical Review Letter