Browsing by Subject "Remission"

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  • Honkamäki, Jasmin; Piirilä, Päivi; Hisinger-Mölkänen, Hanna; Tuomisto, Leena E.; Andersen, Heidi; Huhtala, Heini; Sovijärvi, Anssi; Lindqvist, Ari; Backman, Helena; Lundbäck, Bo; Rönmark, Eva; Lehtimäki, Lauri; Pallasaho, Paula; Ilmarinen, Pinja; Kankaanranta, Hannu (2021)
    BACKGROUND: Child-onset asthma is known to remit with high probability, but remission in adult-onset asthma is seem-ingly less frequent. Reports of the association between remission and asthma age of onset up to late adulthood are scarce. OBJECTIVE: To evaluate the association between asthma remission, age at diagnosis and gender, and assess risk factors of nonremission. METHODS: In 2016, a random sample of 16,000 subjects aged 20 to 69 years from Helsinki and Western Finland were sent a FinEsS questionnaire. Physician-diagnosed asthma was catego-rized by age at diagnosis to early-(0-11 years), intermediate-(12-39 years), and late-diagnosed (40-69 years) asthma. Asthma remission was defined by not having had asthma symptoms and not having used asthma medication in the past 12 months. RESULTS: Totally, 8199 (51.5%) responded, and 879 reported physician-diagnosed asthma. Remission was most common in early-diagnosed (30.2%), followed by intermediate-diagnosed (17.9%), and least common in late-diagnosed asthma (5.0%) (P < .001), and the median times from diagnosis were 27, 18.5, and 10 years, respectively. In males, the corresponding remission rates were 36.7%, 20.0%, and 3.4%, and in females, 20.4%, 16.6%, and 5.9% (gender difference P < .001). In multivariable binary logistic regression analysis, signifi-cant risk factors of asthma nonremission were intermediate (odds ratio [OR] = 2.15, 95% confidence interval: 1.373.36) and late diagnosis (OR = 11.06, 4.82-25.37) compared with early diagnosis, chronic obstructive pulmonary disease (COPD) (OR = 5.56, 1.26-24.49), allergic rhinitis (OR = 2.28, 1.50-3.46), and family history of asthma (OR = 1.86, 1.22-2.85). Results were similar after excluding COPD. CONCLUSION: Remission was rare in adults diagnosed with asthma after age 40 years in both genders. Late-diagnosed asthma was the most significant independent risk factor for nonremission. (C) 2020 American Academy of Allergy, Asthma & Immunology
  • NEO-RACo Study Grp (2018)
    Adverse events (AEs) are common during disease-modifying antirheumatic drug (DMARD) treatment, but their influence on treatment results is unclear. We studied AEs in relation to disease activity in early rheumatoid arthritis (RA). Ninety-nine patients started intensive treatment with three conventional synthetic DMARDs (csDMARDs) and oral prednisolone, and were randomized to a 6-month induction treatment with infliximab or placebo. All AEs during the first 12 months of treatment were recorded. We scored each AE based on severity (scale 1-4) and defined the burden of AEs as the sum of these scores. Patients were divided into tertiles according to the burden of AEs. As outcomes, we assessed 28-joint disease activity score (DAS28) levels and remission rates at 12 and 24 months. Three hundred thirty-one AEs in 99 patients were reported, and 27 (8%) were categorized as severe or serious. Mean burden of AEs per patient was 5.4 +/- 4.3. Seventy-nine AEs (24%) led to temporary (n = 52) or permanent (n = 27) csDMARD discontinuation. Of discontinuations, 1, 21, and 57 were detected in the first, second, and third tertiles, respectively. DAS28 remission rates decreased across tertiles at 12 months (94, 94, and 76%; p for linearity 0.029) and at 24 months (90, 86, and 70%; p for linearity 0.021). Mean DAS28 levels increased across tertiles at 12 months (1.5 +/- 1.0, 1.7 +/- 0.9, and 1.9 +/- 1.2; p for linearity 0.021) and at 24 months (1.4 +/- 0.8, 1.6 +/- 1.0, and 1.9 +/- 1.1; p for linearity 0.007). High burden of AEs is associated with higher disease activity and lower likelihood of remission in early RA.
  • Kuusalo, Laura; Puolakka, Kari; Kautiainen, Hannu; Karjalainen, Anna; Malmi, Timo; Yli-Kerttula, Timo; Leirisalo-Repo, Marjatta; Rantalaiho, Vappu; NEO-RACo Study Grp (2017)
    Identifying prognostic factors for remission in early rheumatoid arthritis (ERA) patients is of key clinical importance. We studied patient-reported outcomes (PROs) as predictors of remission in a clinical trial. We randomized 99 untreated ERA patients to receive remission-targeted treatment with three disease-modifying antirheumatic drugs and prednisolone for 24 months, and infliximab or placebo for the initial 6 months. At baseline, we measured following PROs: eight Short Form 36 questionnaire (SF-36) dimensions, patient's global assessment [PGA, visual analogue scale (VAS)], Health Assessment Questionnaire (HAQ), and pain VAS. We used multivariable-adjusted regression models to identify PROs that independently predicted modified American College of Rheumatology remission at 2 years. Follow-up data at 2 years were available for 93 patients (92%), and 58 patients (62%) were in remission. At baseline, patients who achieved remission had higher radiological score (p = 0.04), lower tender joint count (p = 0.001), lower PGA (p = 0.005) and physician's global assessment (p = 0.019), lower HAQ (p = 0.016), less morning stiffness (p = 0.009), and significantly higher scores in seven out of eight SF-36 dimensions compared with patients who did not. In multivariable models that included all PROs, remission was associated with SF-36 dimensions higher vitality (odds ratio 2.01; 95% confidence interval 1.19-3.39) and better emotional role functioning (odds ratio 1.64; 95% confidence interval 1.01-2.68). PGA, pain VAS, HAQ, and other SF-36 dimensions were not associated with remission. We conclude that self-reported vitality and better emotional role functioning are among the most important PROs for the prediction of remission in ERA.
  • ReACCh-Out NoSPeR Investigators; Rypdal, Veronika (2019)
    Background: Models to predict disease course and long-term outcome based on clinical characteristics at disease onset may guide early treatment strategies in juvenile idiopathic arthritis (JIA). Before a prediction model can be recommended for use in clinical practice, it needs to be validated in a different cohort than the one used for building the model. The aim of the current study was to validate the predictive performance of the Canadian prediction model developed by Guzman et al. and the Nordic model derived from Rypdal et al. to predict severe disease course and non-achievement of remission in Nordic patients with JIA. Methods: The Canadian and Nordic multivariable logistic regression models were evaluated in the Nordic JIA cohort for prediction of non-achievement of remission, and the data-driven outcome denoted severe disease course. A total of 440 patients in the Nordic cohort with a baseline visit and an 8-year visit were included. The Canadian prediction model was first externally validated exactly as published. Both the Nordic and Canadian models were subsequently evaluated with repeated fine-tuning of model coefficients in training sets and testing in disjoint validation sets. The predictive performances of the models were assessed with receiver operating characteristic curves and C-indices. A model with a C-index above 0.7 was considered useful for clinical prediction. Results: The Canadian prediction model had excellent predictive ability and was comparable in performance to the Nordic model in predicting severe disease course in the Nordic JIA cohort. The Canadian model yielded a C-index of 0.85 (IQR 0.83-0.87) for prediction of severe disease course and a C-index of 0.66 (0.63-0.68) for prediction of non-achievement of remission when applied directly. The median C-indices after fine-tuning were 0.85 (0.80-0.89) and 0.69 (0.65-0.73), respectively. Internal validation of the Nordic model for prediction of severe disease course resulted in a median C-index of 0.90 (0.86-0.92). Conclusions: External validation of the Canadian model and internal validation of the Nordic model with severe disease course as outcome confirm their predictive abilities. Our findings suggest that predicting long-term remission is more challenging than predicting severe disease course.
  • Rypdal, Veronika; Guzman, Jaime; Henrey, Andrew; Loughin, Thomas; Glerup, Mia; Arnstad, Ellen D; Aalto, Kristiina; Rygg, Marite; Nielsen, Susan; Herlin, Troels; Fasth, Anders; Berntson, Lillemor; Rypdal, Martin; Nordal, Ellen (BioMed Central, 2019)
    Abstract Background Models to predict disease course and long-term outcome based on clinical characteristics at disease onset may guide early treatment strategies in juvenile idiopathic arthritis (JIA). Before a prediction model can be recommended for use in clinical practice, it needs to be validated in a different cohort than the one used for building the model. The aim of the current study was to validate the predictive performance of the Canadian prediction model developed by Guzman et al. and the Nordic model derived from Rypdal et al. to predict severe disease course and non-achievement of remission in Nordic patients with JIA. Methods The Canadian and Nordic multivariable logistic regression models were evaluated in the Nordic JIA cohort for prediction of non-achievement of remission, and the data-driven outcome denoted severe disease course. A total of 440 patients in the Nordic cohort with a baseline visit and an 8-year visit were included. The Canadian prediction model was first externally validated exactly as published. Both the Nordic and Canadian models were subsequently evaluated with repeated fine-tuning of model coefficients in training sets and testing in disjoint validation sets. The predictive performances of the models were assessed with receiver operating characteristic curves and C-indices. A model with a C-index above 0.7 was considered useful for clinical prediction. Results The Canadian prediction model had excellent predictive ability and was comparable in performance to the Nordic model in predicting severe disease course in the Nordic JIA cohort. The Canadian model yielded a C-index of 0.85 (IQR 0.83–0.87) for prediction of severe disease course and a C-index of 0.66 (0.63–0.68) for prediction of non-achievement of remission when applied directly. The median C-indices after fine-tuning were 0.85 (0.80–0.89) and 0.69 (0.65–0.73), respectively. Internal validation of the Nordic model for prediction of severe disease course resulted in a median C-index of 0.90 (0.86–0.92). Conclusions External validation of the Canadian model and internal validation of the Nordic model with severe disease course as outcome confirm their predictive abilities. Our findings suggest that predicting long-term remission is more challenging than predicting severe disease course.