The Common Point Course.rar

Background and objective: Acute promyelocytic leukemia (APL) (M3 according to FAB classification) is a subtype of acute myelogenous leukemia characterized by a specific t(15;17) (q22;q12) chromosomal translocation. The majority of APL patients achieve morphologic remission after induction chemotherapy. They can be followed from this point by cytogenetic and molecular analysis of the persistence of the PML/RAR alpha transcript. In order to determine the influence of successive courses of consolidation chemotherapy on clinical and molecular outcome, APL patients treated with all-trans retinoic acid (ATRA) and chemotherapy (AIDA-GIMEMA-LAP0493 protocol) were investigated.

The common point course.rar

Design and methods: Twenty-four APL patients (pts) (15 males; 9 females) were studied by RT-PCR and cytogenetic analysis at diagnosis, after induction chemotherapy, at each point after any of three consolidation courses, and every 3 months during the first years of maintenance therapy. The median follow-up was 24 months (mths) (range 7-40 mths).

Failed required course grades, a C+ or below, will be included as part of the assessment of overall grades and grade point average for SAP until the course is repeated or replaced with an equivalent course, and successfully completed.

If HKS determines that the student is not prepared to resume the program with the same academic status at the point where they left off or will not be able to complete the program, HKS will make reasonable efforts at no extra cost to help the student become prepared or to enable the student to complete the program.

Combination Assessment of Ranolazine in Stable Angina (CARISA) was a multi-centre randomised double-blind trial to investigate the effect of ranolazine on the exercising capacity of patients with severe chronic angina [30]. Participants were randomly assigned to one of three arms: twice daily placebo or 750 mg or 1000 mg of ranolazine given over 12 weeks, in combination with standard doses of either atenolol, amlodipine or diltiazem at the discretion of the treating physician. The primary endpoint was treadmill exercise duration at trough, i.e. 12 hours after dosing. The sample size necessary to achieve 90% power was calculated as 462, and expanded to 577 to account for potential dropouts.

After 231 patients had been randomised and followed up for 12 weeks, the investigators undertook a planned blinded sample size re-estimation. This was done to maintain the trial power at 90% even if assumptions underlying the initial sample size calculation were wrong. The standard deviation of the primary endpoint turned out to be considerably higher than planned for, so the recruitment target was increased by 40% to 810. The adaptation prevented an underpowered trial, and as it was conducted in a blinded fashion, it did not increase the type I error rate. Eventually, a total of 823 patients were randomised in CARISA. The trial met the primary endpoint and could claim a significant improvement in exercise duration for both ranolazine doses.

Telmisartan and Insulin Resistance in HIV (TAILoR) was a phase II dose-ranging multi-centre randomised open-label trial investigating the potential of telmisartan to reduce insulin resistance in HIV patients on combination antiretroviral therapy [31]. It used a MAMS design [32] with one interim analysis to assess the activity of three telmisartan doses (20, 40 or 80 mg daily) against control, with equal randomisation between the three active dose arms and the control arm. The primary endpoint was the 24-week change in insulin resistance (as measured by a validated surrogate marker) versus baseline.

Giles et al. conducted a randomised trial investigating three induction therapies for previously untreated, adverse karyotype, acute myeloid leukaemia in elderly patients [33]. Their goal was to compare the standard combination regimen of idarubicin and ara-C (IA) against two experimental combination regimens involving troxacitabine and either idarubicin or ara-C (TI and TA, respectively). The primary endpoint was complete remission without any non-haematological grade 4 toxicities by 50 days. The trial began with equal randomisation to the three arms but then used a response-adaptive randomisation (RAR) scheme that allowed changes to the randomisation probabilities, depending on observed outcomes: shifting the randomisation probabilities in favour of arms that showed promise during the course of the trial or stopping poorly performing arms altogether (i.e. effectively reducing their randomisation probability to zero). The probability of randomising to IA (the standard) was held constant at 1/3 as long as all three arms remained part of the trial. The RAR design was motivated by the desire to reduce the number of patients randomised to inferior treatment arms.

Once funding has been secured, one of the next challenges is to obtain ethics approval for the study. While this step is fairly painless in most cases, we have had experiences where further questions about the AD were raised, mostly around whether the design makes sense more broadly, suggesting unfamiliarity with AD methods overall. These clarifications were easily answered, although in one instance we had to obtain a letter from an independent statistical expert to confirm the appropriateness of the design. In our experience, communications with other stakeholders, such as independent data monitoring committees (IDMCs) and regulators, have been straightforward and at most required a teleconference to clarify design aspects. Explaining simulation results to stakeholders will help to increase their appreciation of the benefits and risks of any particular design, as will walking them through individual simulated trials, highlighting common features of data sets associated with particular adaptations.

In some ADs, multiple hypotheses are tested (e.g. in MAMS trials), or the same hypothesis is re-tested multiple times (e.g. interim and final analyses [91]), or the effects on the primary and key secondary endpoints may be tested group-sequentially [92, 93], all of which may lead to type I error rate inflation. In any (AD or non-AD) trial, the more (often the) null hypotheses are tested, the higher the chance that one will be incorrectly rejected. To control the overall (family-wise) type I error rate at a fixed level (say, 5%), adjustment for multiple testing is necessary [94]. This can sometimes be done with relatively simple methods [95]; however, it may not be possible for all multiple testing procedures to derive corresponding useful CIs.

While this paper focuses on frequentist (classical) statistical methods for trial design and analysis, there is also a wealth of Bayesian AD methods [100] that are increasingly being applied in clinical research [23]. Bayesian designs are much more common for early-phase dose escalation [101, 102] and adaptive randomisation [103] but are gaining popularity also in confirmatory settings [104], such as seamless phase II/III trials [105] and in umbrella or basket trials [106]. Bayesian statistics and adaptivity go very well together [4]. For instance, taking multiple looks at the data is (statistically) unproblematic as it does not have to be adjusted for separately in a Bayesian framework.

The importance of accurately reporting all design specifics, as well as the adaptations made and the trial results, cannot be overemphasised, especially since clear and comprehensive reports facilitate the learning for future (AD or non-AD) trials. Working through our list of recommendations should be a good starting point. These reporting items are currently being formalised, with additional input from a wide range of stakeholders, as an AD extension to the CONSORT reporting guidance and check list.

In 2011, recurrent somatic mutations in genes encoding spliceosome components, including SF3B1, serine and arginine-rich splicing factor 2 (SRSF2), U2 small nuclear RNA auxiliary factor 1 (U2AF1), and zinc finger CCCH-type RNA binding motif and serine/arginine rich 2 (ZRSR2), were first described in patients with MDS [4, 5]. Amongst these, SF3B1 mutations are most common in patients with RARS, accounting for 80% of cases, whereas mutations of other spliceosome components are relatively rare (SRSF2 5.5%; U2AF1 0% [5]). Nearly all SF3B1 mutations are located within the Huntingtin, elongation factor 3, protein phosphatase 2A, and the yeast PI3-kinase TOR1 (HEAT) domains of SF3B1 and occur as heterozygous substitutions. A single mutation (SF3B1K700E) accounts for >50% of SF3B1 mutations in MDS, followed by mutations at the residue K666. Clonal analysis based on the variant allele frequency of SF3B1 and other co-existing mutations revealed that mutations in SF3B1 are present in the dominant clone in most cases. Interestingly, the percentage of BM RS is highly correlated with SF3B1 mutant allele burden [4, 6,7,8], which strongly suggests that mutant SF3B1 directly or indirectly contributes to the formation of RS. In fact, SF3B1 mutations have a high positive predictive value for disease phenotype with RS of 97.7%, whereas the absence of these mutations has an equivalent negative prediction value [7]. These data make SF3B1 the first gene to be strongly related to a specific morphology in myeloid disorders.

According to a large study performed by Broseus et al. [17], patients with MDS/MPN-RS-T have a better median OS than RARS (76 versus 63 months) but an inferior OS when compared to patients with ET (117 months). The leukemic transformation rates are similar in MDS/MPN-RS-T (1.8/100 years) and RARS (2.4/100 years) and higher in MDS/MPN-RS-T in comparison to ET (0.7/100 years). In contrast to RARS, SF3B1 mutations do not seem to have any prognostic impact in MDS/MPN-RS-T. On the other hand, presence of anemia (p = 0.02), abnormal karyotype (p = 0.04), SETBP1 mutations (p = 0.04), and ASXL1 mutations (p = 0.08) have recently been identified as independent predictors of inferior survival in multivariate analysis of 82 patients with MDS/MPN-RS-T [13]. Based on these observations, an HR-weighted prognostic model was developed, in which patients receive 2 points for an abnormal karyotype, 1 point for either SETBP1 and/or ASXL1 mutations, and 1 point for hemoglobin level 041b061a72