Predictive feedback control and Fitts' law

Fitts’ law is a well established empirical formula, known for encapsulating the “speed-accuracy trade-off”. For discrete, manual movements from a starting location to a target, Fitts’ law relates movement duration to the distance moved and target size. The widespread empirical success of the formula is suggestive of underlying principles of human movement control. There have been previous attempts to relate Fitts’ law to engineering-type control hypotheses and it has been shown that the law is exactly consistent with the closed-loop step-response of a time-delayed, first-order system. Assuming only the operation of closed-loop feedback, either continuous or intermittent, this paper asks whether such feedback should be predictive or not predictive to be consistent with Fitts law. Since Fitts’ law is equivalent to a time delay separated from a first-order system, known control theory implies that the controller must be predictive. A predictive controller moves the time-delay outside the feedback loop such that the closed-loop response can be separated into a time delay and rational function whereas a non- predictive controller retains a state delay within feedback loop which is not consistent with Fitts’ law. Using sufficient parameters, a high-order non-predictive controller could approximately reproduce Fitts’ law. However, such high-order, “non-parametric” controllers are essentially empirical in nature, without physical meaning, and therefore are conceptually inferior to the predictive controller. It is a new insight that using closed-loop feedback, prediction is required to physically explain Fitts’ law. The implication is that prediction is an inherent part of the “speed-accuracy trade-off”

Discovery of the peculiar supernova 1998bw in the error box of GRB980425

The discovery of X-ray, optical and radio afterglows of gamma-ray bursts (GRBs) and the measurements of the distances to some of them have established that these events come from Gpc distances and are the most powerful photon emitters known in the Universe, with peak luminosities up to 10^52 erg/s. We here report the discovery of an optical transient, in the BeppoSAX Wide Field Camera error box of GRB980425, which occurred within about a day of the gamma-ray burst. Its optical light curve, spectrum and location in a spiral arm of the galaxy ESO 184-G82, at a redshift z = 0.0085, show that the transient is a very luminous type Ic supernova, SN1998bw. The peculiar nature of SN1998bw is emphasized by its extraordinary radio properties which require that the radio emitter expand at relativistical speed. Since SN1998bw is very different from all previously observed afterglows of GRBs, our discovery raises the possibility that very different mechanisms may give rise to GRBs, which differ little in their gamma-ray properties.Comment: Under press embargo at Nature (submitted June 10, 1998

Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis

BACKGROUND: When subgroup analyses of a positive clinical trial are unrevealing, such findings are commonly used to argue that the treatment's benefits apply to the entire study population; however, such analyses are often limited by poor statistical power. Multivariable risk-stratified analysis has been proposed as an important advance in investigating heterogeneity in treatment benefits, yet no one has conducted a systematic statistical examination of circumstances influencing the relative merits of this approach vs. conventional subgroup analysis. METHODS: Using simulated clinical trials in which the probability of outcomes in individual patients was stochastically determined by the presence of risk factors and the effects of treatment, we examined the relative merits of a conventional vs. a "risk-stratified" subgroup analysis under a variety of circumstances in which there is a small amount of uniformly distributed treatment-related harm. The statistical power to detect treatment-effect heterogeneity was calculated for risk-stratified and conventional subgroup analysis while varying: 1) the number, prevalence and odds ratios of individual risk factors for risk in the absence of treatment, 2) the predictiveness of the multivariable risk model (including the accuracy of its weights), 3) the degree of treatment-related harm, and 5) the average untreated risk of the study population. RESULTS: Conventional subgroup analysis (in which single patient attributes are evaluated "one-at-a-time") had at best moderate statistical power (30% to 45%) to detect variation in a treatment's net relative risk reduction resulting from treatment-related harm, even under optimal circumstances (overall statistical power of the study was good and treatment-effect heterogeneity was evaluated across a major risk factor [OR = 3]). In some instances a multi-variable risk-stratified approach also had low to moderate statistical power (especially when the multivariable risk prediction tool had low discrimination). However, a multivariable risk-stratified approach can have excellent statistical power to detect heterogeneity in net treatment benefit under a wide variety of circumstances, instances under which conventional subgroup analysis has poor statistical power. CONCLUSION: These results suggest that under many likely scenarios, a multivariable risk-stratified approach will have substantially greater statistical power than conventional subgroup analysis for detecting heterogeneity in treatment benefits and safety related to previously unidentified treatment-related harm. Subgroup analyses must always be well-justified and interpreted with care, and conventional subgroup analyses can be useful under some circumstances; however, clinical trial reporting should include a multivariable risk-stratified analysis when an adequate externally-developed risk prediction tool is available

Lack of effect of lowering LDL cholesterol on cancer: meta-analysis of individual data from 175,000 people in 27 randomised trials of statin therapy

<p>Background: Statin therapy reduces the risk of occlusive vascular events, but uncertainty remains about potential effects on cancer. We sought to provide a detailed assessment of any effects on cancer of lowering LDL cholesterol (LDL-C) with a statin using individual patient records from 175,000 patients in 27 large-scale statin trials.</p> <p>Methods and Findings: Individual records of 134,537 participants in 22 randomised trials of statin versus control (median duration 4.8 years) and 39,612 participants in 5 trials of more intensive versus less intensive statin therapy (median duration 5.1 years) were obtained. Reducing LDL-C with a statin for about 5 years had no effect on newly diagnosed cancer or on death from such cancers in either the trials of statin versus control (cancer incidence: 3755 [1.4% per year [py]] versus 3738 [1.4% py], RR 1.00 [95% CI 0.96-1.05]; cancer mortality: 1365 [0.5% py] versus 1358 [0.5% py], RR 1.00 [95% CI 0.93–1.08]) or in the trials of more versus less statin (cancer incidence: 1466 [1.6% py] vs 1472 [1.6% py], RR 1.00 [95% CI 0.93–1.07]; cancer mortality: 447 [0.5% py] versus 481 [0.5% py], RR 0.93 [95% CI 0.82–1.06]). Moreover, there was no evidence of any effect of reducing LDL-C with statin therapy on cancer incidence or mortality at any of 23 individual categories of sites, with increasing years of treatment, for any individual statin, or in any given subgroup. In particular, among individuals with low baseline LDL-C (<2 mmol/L), there was no evidence that further LDL-C reduction (from about 1.7 to 1.3 mmol/L) increased cancer risk (381 [1.6% py] versus 408 [1.7% py]; RR 0.92 [99% CI 0.76–1.10]).</p> <p>Conclusions: In 27 randomised trials, a median of five years of statin therapy had no effect on the incidence of, or mortality from, any type of cancer (or the aggregate of all cancer).</p&gt

NSAID Use Selectively Increases the Risk of Non-Fatal Myocardial Infarction: A Systematic Review of Randomised Trials and Observational Studies

Recent clinical trials and observational studies have reported increased coronary events associated with non steroidal anti-inflammatory drugs (NSAIDs). There appeared to be a disproportionate increase in non-fatal versus fatal events, however, numbers of fatal events in individual studies were too small, and event rates too low, to be meaningful.We undertook a pooled analysis to investigate the effect of NSAIDs on myocardial infarction (MI) risk with the specific aim to differentiate non-fatal from fatal events.We searched Pubmed (January, 1990 to March, 2010) for observational studies and randomised controlled trials that assessed the effect of NSAIDs (traditional or selective COX-2 inhibitors [coxibs]) on MI incidence separately for fatal and non-fatal events. Summary estimates of relative risk (RR) for non-fatal and fatal MIs were calculated with a random effects model.NSAID therapy carried a RR of 1.30 (95% CI, 1.20-1.41) for non-fatal MI with no effect on fatal MI (RR 1.02, 95% CI, 0.89-1.17) in six observational studies. Overall, the risk increase for non-fatal MI was 25% higher (95% CI, 11%-42%) than for fatal MI. The two studies that included only individuals with prior cardiovascular disease presented risk estimates for non-fatal MI on average 58% greater (95% CI, 26%-98%) than those for fatal MI. In nine randomised controlled trials, all investigating coxibs, the pooled RR estimate for non-fatal MI was 1.61 (95% CI, 1.04-2.50) and 0.86 (95% CI 0.51-1.47) for fatal MIs.NSAID use increases the risk of non-fatal MI with no substantial effect on fatal events. Such differential effects, with potentially distinct underlying pathology may provide insights into NSAID-induced coronary pathology. We studied the association between the use of nonsteroidal anti-inflammatory drugs (NSAIDs) and the risk of myocardial infarction (MI), separating non-fatal from fatal events, summarizing the evidence from both observational studies and randomised controlled trials. An increased risk of non-fatal MI was clearly found in both types of studies while use of NSAID did not confer an increased risk of fatal MI. Our findings provide support for the concept that thrombi generated under NSAID treatment could be different from spontaneous thrombi

Relationship between quality of life and psychopathological profile: data from an observational study in children with ADHD

Although ADHD significantly affects the quality of life (QoL) of patients and their families, QoL in children with ADHD has rarely been investigated in association with psychopathological profile, and the relationship remains unclear. The open-label OBSEER study evaluated the effectiveness and tolerability of Equasym XL®, a modified-release methylphenidate, in routine care of children and adolescents (aged 6–17 years) with ADHD. At baseline, questionnaires assessing psychopathological profile (Strengths and Difficulties Questionnaire, SDQ; parental ratings) and QoL (KINDL; parent, child or adolescent versions) were completed; QoL was reassessed at final visit. We analysed the relationship between psychopathology and parent/patient-rated QoL in ADHD at baseline. Data from 721 consecutively referred children and adolescents were analysed. QoL was similarly low from parent and self-ratings and independent of severity on the SDQ subscale hyperactivity/inattention. Self-ratings indicated that additional conduct disorder was associated with further reduction in QoL. Similarly, children with high scores from parent and adolescent ratings on the SDQ subscale conduct problems had reduced QoL on some KINDL subscales. Adolescents with ADHD not receiving medication at baseline reported lower QoL than those already on medication. Results show that children and adolescents with ADHD have low QoL, independent of core symptom severity. Additional conduct problems may further impact QoL negatively, while ADHD medication use may show a trend towards improved QoL. Not all psychopathological problems associated with ADHD affect QoL similarly. As parents appear to have a less critical view of QoL compared with children’s self-ratings, both parent and child ratings should be included in clinical assessments

Forest Fruit Production Is Higher on Sumatra Than on Borneo

BACKGROUND: Various studies have shown that the population densities of a number of forest vertebrates, such as orangutans, are higher on Sumatra than Borneo, and that several species exhibit smaller body sizes on Borneo than Sumatra and mainland Southeast Asia. It has been suggested that differences in forest fruit productivity between the islands can explain these patterns. Here we present a large-scale comparison of forest fruit production between the islands to test this hypothesis. METHODOLOGY/PRINCIPAL FINDINGS: Data on fruit production were collated from Sumatran and Bornean sites. At six sites we assessed fruit production in three forest types: riverine, peat swamp and dryland forests. We compared fruit production using time-series models during different periods of overall fruit production and in different tree size classes. We examined overall island differences and differences specifically for fruiting period and tree size class. The results of these analyses indicate that overall the Sumatran forests are more productive than those on Borneo. This difference remains when each of the three forest types (dryland, riverine, and peat) are examined separately. The difference also holds over most tree sizes and fruiting periods. CONCLUSIONS/SIGNIFICANCE: Our results provide strong support for the hypothesis that forest fruit productivity is higher on Sumatra than Borneo. This difference is most likely the result of the overall younger and more volcanic soils on Sumatra than Borneo. These results contribute to our understanding of the determinants of faunal density and the evolution of body size on both islands

Pleosporales

One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae

Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal

Mounting evidence suggests that there is frequently considerable variation in the risk of the outcome of interest in clinical trial populations. These differences in risk will often cause clinically important heterogeneity in treatment effects (HTE) across the trial population, such that the balance between treatment risks and benefits may differ substantially between large identifiable patient subgroups; the "average" benefit observed in the summary result may even be non-representative of the treatment effect for a typical patient in the trial. Conventional subgroup analyses, which examine whether specific patient characteristics modify the effects of treatment, are usually unable to detect even large variations in treatment benefit (and harm) across risk groups because they do not account for the fact that patients have multiple characteristics simultaneously that affect the likelihood of treatment benefit. Based upon recent evidence on optimal statistical approaches to assessing HTE, we propose a framework that prioritizes the analysis and reporting of multivariate risk-based HTE and suggests that other subgroup analyses should be explicitly labeled either as primary subgroup analyses (well-motivated by prior evidence and intended to produce clinically actionable results) or secondary (exploratory) subgroup analyses (performed to inform future research). A standardized and transparent approach to HTE assessment and reporting could substantially improve clinical trial utility and interpretability