Maudsley Staging Model Research Articles

Effectiveness of electroconvulsive therapy in patients with "less treatment-resistant" depression by the Maudsley Staging Model.

IntroductionElectroconvulsive therapy (ECT) is an effective treatment for patients with mood disorders and is most often used for treatment‐resistant cases. This study aimed to examine the effectiveness of ECT in a real‐world treatment sample in a Chinese psychiatric hospital which included both treatment‐resistant and nontreatment‐resistant patients.MethodsAn observational study of symptom outcomes from admission to the time of discharge was conducted with 37 inpatients diagnosed with unipolar or bipolar depression treated with ECT. Symptom severity was assessed with the 17‐item Hamilton Rating Scales for Depression (HRSD‐17) and treatment‐resistance with the Maudsley Staging Model (MSM). Stratifying at the MSM median admission characteristics and symptom change was compared between patients who were treatment‐resistant (n = 18) and who were not (n = 19). The outcome difference between groups was compared using analyses of covariance adjusted for baseline characteristics including symptom severity, followed by linear regression to identify factors associated symptom improvement in the entire sample.ResultsThe sample (n = 37) showed moderate treatment‐resistance (MSM = 7.30 ± 1.13) at admission and both groups received 8.3 ± 2 ECT sessions. The treatment‐resistant group had a smaller proportion of bipolar patients and more severe symptoms, but showed no significant difference from the nontreatment‐resistant group in HDRS‐17 scores at the time of discharge (adjusted means = 6.23 ± 1.00 vs. 5.94 ± 0.97, Partial η 2 = 0.001, p = .845). Baseline symptom severity was the strongest correlate of reduction in HDRS‐17 scores (β = 0.891, p < .001).ConclusionsSymptom change with ECT in depression did not differ by level of treatment‐resistance but was greatest among those with more severe baseline symptoms. Correlates of ECT effectiveness should be further evaluated in stratified randomized trials.

Is cognitive dysfunction involved in difficult-to-treat depression? Characterizing resistance from a cognitive perspective.

This study aimed to identify clinical and cognitive factors associated with increased risk for difficult-to-treat depression (DTD) or treatment-resistant depression (TRD). A total of 229 adult outpatients with major depression were recruited from the mental health unit at a public hospital. Participants were subdivided into resistant and nonresistant groups according to their Maudsley Staging Model score. Sociodemographic, clinical, and cognitive (objective and subjective measures) variables were compared between groups, and a logistic regression model was used to identify the factors most associated with TRD risk. TRD group patients present higher verbal memory impairment than the nonresistant group irrespective of pharmacological treatment or depressive symptom severity. Logistic regression analysis showed that low verbal memory scores (odds ratio [OR]: 2.02; 95% confidence interval [CI]: 1.38-2.95) together with high depressive symptom severity (OR: 1.29; CI95%: 1.01-1.65) were associated with TRD risk. Our findings align with neuroprogression models of depression, in which more severe patients, defined by greater verbal memory impairment and depressive symptoms, develop a more resistant profile as a result of increasingly detrimental neuronal changes. Moreover, our results support a more comprehensive approach in the evaluation and treatment of DTD in order to improve illness course. Longitudinal studies are warranted to confirm the predictive value of verbal memory and depression severity in the development of TRD.

Molecular serum signature of treatment resistant depression.

A substantial number of patients suffering from major depressive disorder (MDD) do not respond to multiple trials of anti-depressants, develop a chronic course of disease and become treatment resistant. Most of the studies investigating molecular changes in treatment-resistant depression (TRD) have only examined a limited number of molecules and genes. Consequently, biomarkers associated with TRD are still lacking. This study aimed to use recently advanced high-throughput proteomic platforms to identify peripheral biomarkers of TRD defined by two staging models, the Thase and Rush staging model (TRM) and the Maudsley Staging Model (MSM). Serum collected from an inpatient cohort of 65 individuals suffering from MDD was analysed using two different mass spectrometric-based platforms, label-free liquid chromatography mass spectrometry (LC-MS(E)) and selective reaction monitoring (SRM), as well as a multiplex bead based assay. In the LC-MS(E) analysis, proteins involved in the acute phase response and complement activation and coagulation were significantly different between the staging groups in both models. In the multiplex bead-based assay analysis TNF-α levels (log(odds) = -4.95, p = 0.045) were significantly different in the TRM comparison. Using SRM, significant changes of three apolipoproteins A-I (β = 0.029, p = 0.035), M (β = -0.017, p = 0.009) and F (β = -0.031, p = 0.024) were associated with the TRM but not the MSM. Overall, our findings suggest that proteins, which are involved in immune and complement activation, may represent potential biomarkers that could be used by clinicians to identify high-risk patients. Nevertheless, given that the molecular changes between the staging groups were subtle, the results need to be interpreted cautiously.

Staging methods for treatment resistant depression. A systematic review

Treatment resistant depressant (TRD) is classified in different staging models, but these are not used routinely. We aimed to identify staging models for TRD and compare them regarding predictive utility and reliability. Systematic review of Pubmed, Embase and PsycINFO (1985-January 2010) without language limits, plus articles identified from reference lists of previous reviews. We excluded articles focusing on TRD treatment. We qualitatively summarized characteristics of the identified staging models, describing strengths and limitations for each model. If available, we reported results of validation studies. From 950 retrieved articles five staging models were found; the Antidepressant Treatment History Form, Thase and Rush Model, European Staging Model, Massachusetts General Hospital Staging model and the Maudsley Staging Model (MSM). Six studies investigated the predictive utility (of four models). We observed an evolution from single antidepressant adequacy ratings, towards a multidimensional and more continuous scored staging model which also introduced TRD characteristics (severity and duration). The operationalization criteria improved; the scoring of different treatment strategies (between/within class switching and augmentation/combination) changed according to the existing evidence. Over time, efforts to validate models improved. The predictive utility was assessed best for the MSM. Few staging models existed; their reliability was hardly assessed. Despite validation of the MSM, further investigation of the reliability and predictive utility of TRD staging models and additional disease characteristics is required. Correct staging of TRD might improve generalizability of results from clinical studies and improve delivery of care to TRD patients. We propose methods to validate staging models in TRD.