Prognostic categories for amyotrophic lateral sclerosis

Scotton, William; Scott, Kirsten M.; Moore, Dan H.; Almedom, Leeza; Wijesekera, Lokesh; Janssen, Anna; Nigro, Catherine; Sakel, Mohammed; Leigh, P. Nigel; Shaw, Christopher E.; Al‐Chalabi, Ammar

doi:10.3109/17482968.2012.679281

Cited by 25 publications

(18 citation statements)

References 27 publications

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“…Contrary to former statements [11], but in concordance with Scotton et al [35], we believe that it is possible to predict the survival probability at the time of diagnosis for an individual patient with some range of uncertainty. Taking into account the age and gender of the patient, the interval between onset and diagnosis, the site of onset, early cognitive decline, the extent of clinical involvement due to EEC and ALS-FRS, and the partnership status, an almost accurate future prognosis of an individual patient seems feasible.…”

Section: Resultscontrasting

confidence: 52%

Factors Predicting Survival in ALS Patients - Data from a Population-Based Registry in Rhineland-Palatinate, Germany

Wolf

Safer²,

Wöhrle³

et al. 2015

Neuroepidemiology

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Background: The possibility to survive with amyotrophic lateral sclerosis (ALS) varies considerably and survival extends from a few months to several years. A number of demographic and clinical factors predicting survival have been described; however, existing data are conflicting. We intended to predict patient survival in a population-based prospective cohort of ALS patients from variables known up to the time of diagnosis. Methods: Incident ALS patients diagnosed within three consecutive years were enrolled and regularly followed up. Candidate demographic and disease variables were analysed for survival probability using the Kaplan-Meier method. The Cox proportional hazard regression model was used to assess the influence of selected predictor variables on survival prognosis. Results: In the cohort of 193 patients (mean age 65.8, standard deviation 10.2 years), worse prognosis was independently predicted by older age, male gender, bulbar onset, probable or definite ALS according to El Escorial criteria, shorter interval between symptom onset and diagnosis, lower Functional Rating Scale, diagnosis of frontotemporal dementia, and living without a partner. Conclusions: Taking into account these predictor variables, an approximate survival prognosis of individual ALS patients at diagnosis seems feasible.

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Section: Resultscontrasting

confidence: 52%

Factors Predicting Survival in ALS Patients - Data from a Population-Based Registry in Rhineland-Palatinate, Germany

Wolf

Safer²,

Wöhrle³

et al. 2015

Neuroepidemiology

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“…Previous studies made use of prognostic categories for survival in ALS by applying prognostic models or staging systems [5,42]. As far as we know, there are no studies about the validity and applicability of comparable models and systems for functional status.…”

Section: Discussionmentioning

confidence: 99%

“…In clinical practice, individual prognostication with regard to disability progression and the timing of supportive interventions are largely based on the clinician's cumulated experience. Despite attempts to construct prognostic algorithms for survival, prognostic tools for the functional course in ALS are lacking [5,6]. Evidence on prognostic factors for disability progression may enhance clinical prediction and guide clinical decision making, including patient counseling and treatment selection [7,8].…”

Section: Introductionmentioning

confidence: 99%

Prognostic factors for the course of functional status of patients with ALS: a systematic review

et al. 2014

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The progressive course of amyotrophic lateral sclerosis (ALS) results in an ever-changing spectrum of the care needs of patients with ALS. Knowledge of prognostic factors for the functional course of ALS may enhance clinical prediction and improve the timing of appropriate interventions. Our objective was to systematically review the evidence regarding prognostic factors for the rate of functional decline of patients with ALS, assessed with versions of the ALS Functional Rating Scale (ALSFRS). Two reviewers independently assessed the methodological quality of the thirteen included studies using the Quality in Prognosis Studies (QUIPS) tool. The overall quality of evidence for each prognostic factor was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, considering risk of bias, imprecision, inconsistency, indirectness, and publication bias. The quality of evidence for the prognostic value of age at onset, site of onset, time from symptom onset to diagnosis, and ALSFRS-Revised baseline score was low, mainly due to the limited data and inconsistency of results in the small number of studies included. The prognostic value of initial rate of disease progression, age at diagnosis, forced vital capacity, frontotemporal dementia, body mass index, and comorbidity remains unclear. We conclude that the current evidence on prognostic factors for functional decline in ALS is insufficient to allow the development of a prediction tool that can support clinical decisions. Given the limited data, future prognostic studies may need to focus on factors that have a predictive value for a decline in ALSFRS(-R) domain scores, preferably based on internationally collected and shared data.

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“…Previously published prognostic models have reported conflicting data regarding the reliability of prognostic factors such age, gender, El Escorial diagnostic category [1, 3, 20, 21, 26, 30–32]. Environmental factors such as smoking, socio-economic status, marital status, and multidisciplinary care have also been reported to affect prognosis in ALS [26, 32, 33].…”

Section: Discussionmentioning

confidence: 99%

Predicting prognosis in amyotrophic lateral sclerosis: a simple algorithm

et al. 2015

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The objective of the study was to develop and validate a practical prognostic index for patients with amyotrophic lateral scleroses (ALS) using information available at the first clinical consultation. We interrogated datasets generated from two population-based projects (based in the Republic of Ireland and Italy). The Irish patient cohort was divided into Training and Test sub-cohorts. Kaplan–Meier methods and Cox proportional hazards regression were used to identify significant predictors of prognoses in the Training set. Using a weighted grading system, a prognostic index was derived that separated three risk groups. The validity of index was tested in the Irish Test sub-cohort and externally confirmed in the Italian replication cohort. In the Training sub-cohort (n = 117), significant predictors of prognoses were site of disease onset (HR = 1.7, p = 0.012); ALSFRS-R slope prior to first evaluation (HR = 2.8, p < 0.0001), and executive dysfunction (HR = 2.11, p = 0.001). The risk group system generated using these results predicted median survival time in the Training set, the Test set (n = 87) and the Italian cohort (n = 122) with no overlap of the 95 % CI (p < 0.0001). In the validation cohorts, a high-risk classification was associated with a positive predictive value for poor prognosis of 73.3–85.7 % and a negative predictive value (NPV) for good prognosis of 93.3–100 %. Classification into the low-risk group was associated with an NPV for bad prognosis of 100 %. A simple algorithm using variables that can be gathered at first patient encounter, validated in an independent patient series, reliably predicts prognoses in ALS patients.

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Prognostic categories for amyotrophic lateral sclerosis

Cited by 25 publications

References 27 publications

Factors Predicting Survival in ALS Patients - Data from a Population-Based Registry in Rhineland-Palatinate, Germany

Factors Predicting Survival in ALS Patients - Data from a Population-Based Registry in Rhineland-Palatinate, Germany

Prognostic factors for the course of functional status of patients with ALS: a systematic review

Predicting prognosis in amyotrophic lateral sclerosis: a simple algorithm

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