Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change

Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes

Minimum detectable and minimal clinically important changes for pain in patients with nonspecific neck pain

<p>Abstract</p> <p>Background</p> <p>The minimal detectable change (MDC) and the minimal clinically important changes (MCIC) have been explored for nonspecific low back pain patients and are similar across different cultural settings. No data on MDC and MCIC for pain severity are available for neck pain patients. The objectives of this study were to estimate MDC and MCIC for pain severity in subacute and chronic neck pain (NP) patients, to assess if MDC and MCIC values are influenced by baseline values and to explore if they are different in the subset of patients reporting referred pain, and in subacute versus chronic patients.</p> <p>Methods</p> <p>Subacute and chronic patients treated in routine clinical practice of the Spanish National Health Service for neck pain, with or without pain referred to the arm, and a pain severity ≥ 3 points on a pain intensity number rating scale (PI-NRS), were included in this study. Patients' own "global perceived effect" over a 3 month period was used as the external criterion. The minimal detectable change (MDC) was estimated by means of the standard error of measurement in patients who self-assess as unchanged. MCIC were estimated by the mean value of change score in patients who self-assess as improved (mean change score, MCS), and by the optimal cutoff point in receiver operating characteristics curves (ROC). The effect on MDC and MCIC of initial scores, duration of pain, and existence of referred pain were assessed.</p> <p>Results</p> <p>658 patients were included, 487 of them with referred pain. MDC was 4.0 PI-NRS points for neck pain in the entire sample, 4.2 for neck pain in patients who also had referred pain, and 6.2 for referred pain. MCS was 4.1 and ROC was 1.5 for referred and for neck pain, both in the entire sample and in patients who also complained of referred pain. ROC was lower (0.5 PI-NRS points) for subacute than for chronic patients (1.5 points). MCS was higher for patients with more intense baseline pain, ranging from 2.4 to 4.9 PI-NRS for neck pain and from 2.4 to 5.3 for referred pain.</p> <p>Conclusion</p> <p>In general, improvements ≤ 1.5 PI-NRS points could be seen as irrelevant. Above that value, the cutoff point for clinical relevance depends on the methods used to estimate MCIC and on the patient's baseline severity of pain. MDC and MCIC values in neck pain patients are similar to those for low back pain and other painful conditions.</p

Moult cycle specific differential gene expression profiling of the crab Portunus pelagicus

Background: Crustacean moulting is a complex process involving many regulatory pathways. A holistic approach to examine differential gene expression profiles of transcripts relevant to the moulting process, across all moult cycle stages, was used in this study. Custom cDNA microarrays were constructed for Portunus pelagicus. The printed arrays contained 5000 transcripts derived from both the whole organism, and from individual organs such as the brain, eyestalk, mandibular organ and Y-organ from all moult cycle stages.Results: A total of 556 clones were sequenced from the cDNA libraries used to construct the arrays. These cDNAs represented 175 singletons and 62 contigs, resulting in 237 unique putative genes. The gene sequences were classified into the following biological functions: cuticular proteins associated with arthropod exoskeletons, farnesoic acid O-methyltransferase (FaMeT), proteins belonging to the hemocyanin gene family, lectins, proteins relevant to lipid metabolism, mitochondrial proteins, muscle related proteins, phenoloxidase activators and ribosomal proteins. Moult cycle-related differential expression patterns were observed for many transcripts. Of particular interest were those relating to the formation and hardening of the exoskeleton, and genes associated with cell respiration and energy metabolism.Conclusions: The expression data presented here provide a chronological depiction of the molecular events associated with the biological changes that occur during the crustacean moult cycle. Tracing the temporal expression patterns of a large variety of transcripts involved in the moult cycle of P. pelagicus can provide a greater understanding of gene function, interaction, and regulation of both known and new genes with respect to the moulting process