O R I G I N A L C O M M U N I C A T I O N
Sniff nasal inspiratory pressure as a prognostic factor
of tracheostomy or death in amyotrophic lateral sclerosis
Rosa Capozzo•Vitaliano N. Quaranta•Fabio Pellegrini •Andrea Fontana•Massimiliano Copetti•Pierluigi Carratu` •Francesco Panza•Anna Cassano•
Vito A. Falcone•Rosanna Tortelli•Rosa Cortese•Isabella L. Simone•
Onofrio Resta•Giancarlo Logroscino
Received: 26 September 2014 / Revised: 4 December 2014 / Accepted: 6 December 2014 / Published online: 19 December 2014 Ó Springer-Verlag Berlin Heidelberg 2014
Abstract Forced vital capacity (FVC) shows limitations in detecting respiratory failure in the early phase of amyotrophic lateral sclerosis (ALS). In fact, mild-to-moderate respiratory muscle weakness may be present even when FVC is normal, and ALS patients with bulbar involvement might not be able to perform correctly the spirometry test. Sniff nasal inspiratory pressure (SNIP) is correlated with transdiaphragmatic strength. We evaluated SNIP at baseline as a prognostic factor of tracheostomy or death in patients with ALS. In a multidisciplinary tertiary care center for motorneuron disease, we enrolled 100
patients with ALS diagnosed with El Escorial criteria in the period between January 2006 and December 2010. Main outcome measures were tracheostomy or death. RECursive Partitioning and AMalgamation (RECPAM) analysis was also used to identify subgroups at different risks for the tracheostomy or death. Twenty-nine patients with ALS reached the outcome (12 died and 17 had tra-cheostomy). Using a multivariate model SNIP correctly classified the risk of the composite event within 1 year of follow-up with a continuous Net Reclassification Improvement cNRI of 0.58 (p = 0.03). Sex, Amyotrophic Lateral Sclerosis Functional Rating Scale revisited, site of onset, and FVC did not improve the classification of prognostic classes. SNIP B18 cmH2O identified the
RECPAM class with the highest risk (Class 1, hazard ratio = 9.85, 95 % confidence interval: 2.67–36.29, p\ 0.001). SNIP measured at baseline identified patients with ALS with initial respiratory failure. Finally, using only ALS patients with spinal onset of the disease, our findings were mostly overlapping with those reported in the models including the whole sample. At baseline, SNIP appeared to be the best predictor of death or tracheostomy within 1 year of follow-up. The measurement of SNIP in the early phase of the disease may contribute to identify patients with high risk of mortality or intubation. SNIP may also provide an additional tool for baseline stratifi-cation of patients with ALS in clinical trials.
Keywords SNIP FVC Prognosis Respiratory function ALS
Abbreviations
ALS Amyotrophic lateral sclerosis ALSFRS-R Revised amyotrophic lateral sclerosis
Functional Rating Scale Electronic supplementary material The online version of this
article (doi:10.1007/s00415-014-7613-3) contains supplementary material, which is available to authorized users.
R. Capozzo F. Panza R. Tortelli R. Cortese I. L. Simone G. Logroscino (&)
Neuroscience and Sense Organs, Department of Basic Medical Science, Neurodegenerative Diseases Unit, University of Bari ‘‘Aldo Moro’’, Bari, Italy
e-mail: giancarlo.logroscino@uniba.it V. N. Quaranta P. Carratu` A. Cassano V. A. Falcone O. Resta
Pulmonary Disease Institute, University of Bari ‘‘Aldo Moro’’, Bari, Italy
F. Pellegrini A. Fontana M. Copetti
Unit of Biostatistics, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, FG, Italy
F. Pellegrini
Unit of Biostatistics, Consorzio Mario Negri Sud, Santa Maria Imbaro, CH, Italy
F. Panza R. Tortelli G. Logroscino
Department of Clinical Research in Neurology, University of Bari ‘‘Aldo Moro’’, ‘‘Pia Fondazione Cardinale G. Panico’’, Tricase, LE, Italy
AUC Area under the receiver operating characteristic Curve
BDI Beck Depression Inventory
EI Executive index
FAB Frontal Assessment Battery FVC Forced vital capacity FTD Frontotemporal dementia NIV Noninvasive ventilation MMSE Mini-Mental State Examination MMT Manual muscle testing
MoCA Montreal Cognitive Assessment 95 % CI 95 % confidence intervals
RECPAM RECursive Partitioning and Amalgamation ROC Receiver-operating characteristic
SD Standard deviation
SDMT Symbol Digit Modalities Test-Oral version
ST Stroop test
VFT Verbal Fluency Test
Introduction
Amyotrophic lateral sclerosis (ALS) is a progressive neu-rodegenerative disorder involving motorneurons. Most ALS deaths are due to the impairment of pulmonary functions resulting from respiratory muscles weakness [1]. Manage-ment of respiratory failure is based on non-invasive venti-lation (NIV) or tracheostomy with fully informed consent may be offered when NIV is no longer effective [2]. Some patients with ALS require early respiratory support, while others may have a relatively prolonged survival [3]. Non-respiratory factors including female gender, advanced age, short interval symptoms onset-to-diagnosis, bulbar onset, altered nutritional status, and low score of Amyotrophic Lateral Sclerosis Functional Rating Scale revisited (ALS-FRSr) are associated with shorter survival [4].
Forced vital capacity (FVC) is an index of respiratory failure commonly used to evaluate the respiratory dys-function in patients with ALS [5]. FVC B50 % of the standardized predicted value has been correlated to a poor prognosis [6]. FVC is important for clinical planning and stratification in clinical trials of patients with ALS [7,8], but it may not be an ideal test to diagnose respiratory dysfunctions in the early phase of ALS. In fact, given the sigmoid relationship of the lung pressure–volume curve [9], FVC may not fall until the development of a severe muscle weakness. Mild-to-moderate respiratory muscle weakness may be present even when FVC is normal [10]. Furthermore, patients with bulbar involvement might not be able to perform correctly the spirometry test [11], requiring the full activation of respiratory muscles.
Sniff nasal inspiratory pressure (SNIP), described in 1985 as an alternative test to assess respiratory functions [12], is a noninvasive maneuver which consists of mea-suring nasal pressure through a plug occluding one nostril during a maximal sniff performed through the contralateral nostril, from current volume. SNIP correlates with trans-diaphragmatic strength and is sensible to small changes in respiratory functions [13,14]. SNIP may give information about survival in patients with ALS [15,16]. The aim of this study was to estimate the prognostic value of SNIP measured at baseline in a cohort of patients with ALS within 1 year of follow-up.
Methods
The present study was conducted according to the World Medical Association’s 2008 Declaration of Helsinki and the guidelines for Good Clinical Practice and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) [17]. In this retrospective cohort study, we enrolled 100 patients with ALS referred to the multidisciplinary center for motorneuron disease at the University of Bari ‘‘Aldo Moro’’ in the period January 2006–December 2010. All ALS patients were diagnosed according to El Escorial criteria [18]. At baseline, the following variables were measured: sex, age, body mass index (BMI, kg/m2), date of onset of first symptom, date of diagnosis, ALSFRSr [19], FVC, SNIP, arterial partial pressure of oxygen, carbon dioxide, and Charlson Comorbidity Index (CCI) [20]. Patients were classified in bulbar or spinal-onset, referring to the presence of motor neuron signs in bulbar or spinal regions as their first reported symptoms. The outcomes were tracheostomy or death. Patients who neither underwent tracheostomy nor died, were considered censored assuming January 31st, 2011 as date of the final outcome. Our study protocol was approved by Local Ethical Committee and written informed consent was obtained from all patients.
Respiratory tests were performed by experienced tech-nicians under the supervision of a pneumologist. Spirom-etry was performed by a qualified respiratory technician (Spirometer PK Morgan Ldt; Gillingham, UK). The equipment was calibrated using a 3-L syringe and the analysis was performed according to the American Tho-racic Society (ATS)/European Respiratory Society (ERS) Guidelines [21]. The FVC value was measured in sitting position. The best of three reproducible values, expressed as a percentage of the predictive normal value, was taken into account. To overcome air leakage from the mouth, a full-face mask was adapted for bulbar ALS patients. The sniff test (performed with the MicroRPM-Respiratory Pressure Meter) was used to assess the SNIP value in
sitting position. SNIP is measured in one nostril during a maximal sniff performed through the contralateral nostril closed by a sealing plug. Patients were asked to breathe normally with a closed mouth and to perform at least five maximal sniffs, each separated by 30 s. The highest of recorded values sustained for over 1 s was recorded. The following criteria were used to select a suitable sniff: (a) a pressure curve showing a regular upstroke and a sharp peak and (b) a total sniff duration of less than 0.5 s [22] The plug-catheter was inserted in one nostril and the other extremity of the catheter was connected to a pressure transducter. The pressure was expressed in cmH2O. The
patients were instructed to take a series of short sniffs with the mouth closed; the highest of five results was recorded. Statistical analysis
Patients baseline characteristics were reported as frequency (percentages) and mean ± standard deviation (SD), or median and range, and comparisons between patients groups were performed using Pearson Chi-square and two-sample t test (or Mann–Whitney U test as appropriated), for categorical and continuous variables, respectively. To test the presence of a linear trend across ordinal variables, Mantel–Haenszel Chi-square test was performed. Inci-dence rates for events (i.e., tracheostomy/death) were reported for 100 person-years. Pearson’s correlation coef-ficients were estimated to assess associations between continuous variables. Time-to-event analysis was per-formed with univariate and multivariate Cox proportional hazards regression models and risks were reported as hazard ratios (HR) along with their 95 % confidence interval (95 % CI). Time variable was defined as the time between the date of the first visit (baseline) and tracheos-tomy/death (whichever occurred first). Disease duration was defined as the time between disease onset and the date of the first visit. For subjects who did not experience any event, time variable was defined as the time between the baseline and the date of the last available clinical follow-up. The assumption of proportionality of the hazards was tested by using scaled Schoenfeld residuals.
Two multivariate models were estimated. The first one was a clinical-based model which included: age, sex, BMI, CCI, ALSFRSr, FVC, site of onset, disease duration (‘‘Base’’ model). The second model included the SNIP variable as new predictor (‘‘Base plus SNIP’’ model). HR estimates for disease duration were reported for each uni-tary increase of 5 years. Improvements in model’s dis-criminatory power and risk reclassification provided by SNIP, within 1 year of follow-up, were assessed by mod-ified c-statistic for censored survival data and the survival-based continuous Net Reclassification Improvement (cNRI) [23], respectively, using predicted probabilities
from multivariate Cox regressions. Furthermore, a sensi-tivity analysis to evaluate the net risk reclassification within a time horizon of 1, 1.5, 2, 2.5, and 3 years with different arbitrarily small positive quantities (epsilon) of differences in models’ risk probabilities was performed.
Models’ calibration was assessed using the survival-based Hosmer–Lemeshow goodness-of-fit test. Moreover, the receiver operating characteristic (ROC) curve analysis was used to detect the optimal cut-off both for SNIP and FVC, which jointly maximize the sensitivity and the specificity to detect events within 1 year of follow-up, also providing the area under the ROC curve (AUC). Finally, interactions between patients’ characteristics on the pre-diction of events risk were investigated using RECursive Partitioning and AMalgamation (RECPAM) algorithm, along with an internal validation of splits using a permu-tation approach. Sex, ALSFRSr, site of onset, FVC, and SNIP were included as candidate splitting variables, whereas age, CCI, and disease duration were used as global adjustment variables. Adjusted survival curves obtained from the RECPAM model were also reported. Finally, both univariate and multivariate Cox models using only spinal-onset ALS patients have been performed. A p value \0.05 was considered statistically significant. All statistical analyses were performed using SAS Release 9.3 (SAS Institute, Cary, NC, USA).
Results
Overall 29 of 100 patients (143 person-years, incidence rate: 20.25 %) died or had tracheostomy (12 deaths, 17 tracheostomy). The median follow-up time was 1.20 years (range 0.02–3.89 years). When patients were censored within 1 year of follow-up, the incidence of the composite event was 12 out of 85 person-years (cumulative incidence 14.07 %). Patients baseline characteristics also divided by the composite event status are reported in Table1. In the whole sample, SNIP median value was 43.5 cmH2O
(7.0–119.0), FVC median value was 81.6 % (20.3–131.0); mean age was 62.08 ± 10 years, 55 % were male, mean disease duration was 1.75 ± 1.63 years, 69 % of patients had spinal onset. SNIP was positively correlated to FVC (r = 0.47, p \ 0.001). Patients who experienced trache-ostomy or death presented significant differences in SNIP (p \ 0.001) and FVC values at baseline (p = 0.023) compared to patients who did not reach the outcomes. Results from univariate Cox regression are reported in Table2.
Only SNIP (HR 0.98, 95 % CI 0.96–0.99, p = 0.005), FVC (HR 0.99, 95 % CI 0.97–1.00, p = 0.043), and ALSFRSr (HR 0.95, 95 % CI 0.91–0.99, p = 0.026) resulted significantly associated with the composite event.
Although not statistically significant, subjects with spinal onset of disease had a decreased risk of the composite event (HR 0.56, 95 % CI 0.27–1.18, p = 0.128). Further-more, the SNIP variable was categorized into units of 10 cmH2O below 70 cmH2O as following and related to
the composite event: (1) C70; (2) between 50 and 70 (excluded); (3) between 40 and 50 (excluded); (4) between 30 and 40 (excluded); (5)\30. A univariate Cox regression was performed to assess the statistical association of this
categorization with the composite outcome. As expected, a statistically significant association was found for categori-cal SNIP (HR 1.39, 95 % CI 1.07 and 1.81, p = 0.013). Patients with SNIP at baseline \50 cmH2O had a higher
risk to experience the composite event than patients with SNIP [70 cmH2O (p value for linear trend \0.001)
(Fig.1).
Results of Cox multivariate models are reported in Table3. In both ‘‘Base’’ and ‘‘Base ? SNIP’’ models, FVC Table 1 Baseline
characteristics of patients with amyotrophic lateral sclerosis divided by the composite event status
BMI body mass index, ALSFRSr Amyotrophic Lateral Sclerosis Functional Rating Scale revisited, SNIP sniff nasal inspiratory pressure, FVC forced vital capacity * p values from two-sample t test and Chi-squared test for continuous and categorical variables, respectively ^ p value from Mann–Whitney U test
# p values from two-sample t test using log-transformed values
Variable Category All subjects Events
(tracheostomized/ death patients)
Non-events p value*
No. of patients 100 29 71
Age (years) Mean ± SD 62.08 ± 10.00 64.20 ± 8.09 61.25 ± 10.59 0.187 Median (min– max) 62.69 (36.59–81.30) 64.44 (46.60–78.27) 61.40 (36.59–81.30) Sex (n, %) Females 45 (45.00 %) 14 (48.28 %) 31 (43.66 %) 0.674 Males 55 (55.00 %) 15 (51.72 %) 40 (56.34 %) BMI (kg/m2) Mean ± SD 25.45 ± 3.99 25.15 ± 4.48 25.58 ± 3.80 0.627 Median (min– max) 25.28 (16.85–40.90) 24.22 (17.30–35.36) 25.39 (16.85-40.90) ALSFRSr Mean ± SD 36.76 ± 7.23 34.83 ± 9.58 37.55 ± 5.92 0.338^ Median (min– max) 38.00 (10.00–48.00) 38.00 (10.00–48.00) 38.00 (20.00-48.00) Charlson Comorbidity Index Mean ± SD 1.25 ± 1.11 1.14 ± 1.19 1.30 ± 1.09 0.398^ Median (min– max) 1.00 (0.00–4.00) 1.00 (0.00–4.00) 1.00 (0.00–4.00)
Site of onset (n, %) Bulbar 31 (31.00 %) 12 (41.38 %) 19 (26.76 %) 0.152 Spinal 69 (69.00 %) 17 (58.62 %) 52 (73.24 %)
Disease duration, from the onset to the first assessment (years) Mean ± SD 1.75 ± 1.63 1.34 ± 0.75 1.92 ± 1.85 0.283# Median (min– max) 1.41 (0.01–13.53) 1.36 (0.14–3.12) 1.42 (0.01–13.53) B1.4 years (median) 49 (49.00 %) 15 (51.72 %) 34 (47.89 %) 0.727 [1.4 years (median) 51 (51.00 %) 14 (48.28 %) 37 (52.11 %) SNIP (cmH2O) Mean ± SD 47.78 ± 25.75 32.97 ± 20.95 53.83 ± 25.18 \0.001 Median (min– max) 43.50 (7.00–119.00) 32.00 (7.00–96.00) 51.00 (14.00–119.00) FVC (%) Mean ± SD 78.37 ± 25.45 69.34 ± 23.67 82.06 ± 25.39 0.023 Median (min– max) 81.60 (20.30–131.00) 72.80 (27.00–122.20) 83.00 (20.30–131.00) Follow-up (years) Mean ± SD 1.43 ± 0.91 1.17 ± 0.66 1.54 ± 0.98 0.033#
Median (min– max)
was not statistically associated with the risk of composite event, whereas SNIP was associated to a better outcome (HR 0.98, 95 % CI 0.96–0.99, p = 0.038). At one-year follow-up, the ‘‘Base’’ model yielded a survival c-statistic of 0.84 (95 % CI 0.71–0.97) and a calibration p value of 0.98. The ‘‘Base ? SNIP’’ model, yielded survival c-sta-tistic of 0.91 (95 % CI 0.85–0.96), and calibration p value of 0.99. The p value for the difference between the two survival c-statistics was p = 0.069. The optimal cut-off for SNIP was 34 cmH2O (i.e., patients with SNIP \34 cmH2O
were classified to develop the event within 1 year of fol-low-up). Such cut-off achieved a sensitivity of 0.75 (95 % CI 0.47–0.91), a specificity of 0.72 (95 % CI 0.63–0.81), a positive predictive value (PPV) of 0.27 (95 % CI 0.12–0.42), a negative predictive value of (NPV) of 0.95 (95 % CI 0.88–0.98). The overall discriminatory power for SNIP was 0.80 (AUC). The discriminatory power for FVC was lower (AUC = 0.57) and the optimal-estimated cut-off was 75.9 (even patients with FVC\75.9 were classified to develop the event within 1 year of follow-up), with a sensitivity of 0.58 (95 % CI 0.32–0.81), a specificity of 0.58 (95 % CI 0.47–0.68), a PPV of 0.16 (95 %CI 0.05–0.27) and a NPV of 0.91 (95 % CI 0.81–0.96). The addition of SNIP into the multivariate model correctly reclassified the risk of the composite events in the 31 % of events and in the 27.2 % of non-events, respectively, achieving a cNRI of 0.58 (p = 0.036). Details of model comparisons are reported in Table4. Sensitivity analysis for reclassification in terms of cNRI is reported in Sup-plemental Table 1. The added value of SNIP as predictor is consistently confirmed according to different time horizons for model prediction and non-zero (i.e., more conservative) increase or decrease in reclassification.
Figure2 shows the results of the tree-based RECPAM analysis, where risks of tracheotomy/death was stratified according to SNIP levels, adjusted for global variables (age at the first visit, CCI, and disease duration). Indeed, the algorithm identified three subgroups of patients at different risk for the event. The reference class (Class 3) is repre-sented by the subgroup with the lowest incidence, and all the HRs were estimated with respect to the reference class. A SNIP cutoff value [51 cmH2O identified the reference
class (HR = 1), whereas a SNIP cutoff value B18 cmH2O
identified the class with the highest risk for the composite event (Class 1, HR 9.85, 95 % CI 2.67–36.29, p \ 0.001). Table 2 Univariate Cox regression models for amyotrophic lateral
sclerosis patients. Risks are reported as hazard ratios (HR) along with their 95 % confidence interval (95 % CI)
Variable Category HR 95 % CI Age 1.023 0.985–1.062 Sex Males vs. females 1.000 0.481–2.077 BMI 0.998 0.907–1.099 Charlson Comorbidity Index 0.901 0.636–1.275 ALSFRSr 0.951 0.911–0.994
Site of onset Spinal vs. bulbar 0.561 0.267–1.180 Disease durationa 0.257 0.047–1.396
FVC 0.986 0.972–1.000
SNIP (categorical)b 1.394 1.073–1.812 SNIP (continuous) 0.975 0.958–0.992 a Estimated HR for each unitary increase of 5 years in disease duration
b Estimated HR for each unitary increment in SNIP category [i.e., \30 vs. (30–40), (30–40) vs. (40–50), (40–50) vs. (50–70) and (50–70) vs. C70]
BMI body mass index, ALSFRSr Amyotrophic Lateral Sclerosis Functional Rating Scale revisited, SNIP sniff nasal inspiratory pres-sure, FVC forced vital capacity
Fig. 1 Histogram of patients with amyotrophic lateral sclerosis (percentage frequency distribution) within each sniff nasal inspiratory pressure (SNIP) category. The two sets of bars distinguish events and non-events, respectively. Dashed line represents the functional shape of number of events across SNIP values
Furthermore, SNIP values between 18 and 51 cmH2O
identified the intermediate risk class (Class 2, HR 3.53, 95 %CI 1.14–10.91, p = 0.028). Although included as candidate splitting variables into the RECPAM algorithm, sex, ALSFRSr, site of onset, and FVC did not contribute to the identification of further prognostic classes of risk, as
well as did not enter the final RECPAM model when introduced in a stepwise fashion as main effects. The adjusted survival curves identified by RECPAM were shown in Fig. 3. Most importantly, as shown in Supple-mental Table 2, the addition of RECPAM tree-structured SNIP into the ‘‘Base’’ model (i.e., ‘‘Base ? SNIP’’ model) Table 3 Multivariate Cox regression models for amyotrophic lateral sclerosis patients
Model Variable Category HR 95 % CI
Base Age 1.012 0.971–1.054
Sex Males vs. females 0.864 0.364–2.052
BMI 1.052 0.951–1.164
Charlson Comorbidity Index 0.850 0.580–1.245
ALSFSr 0.956 0.904–1.011
Site of onset Spinal vs. bulbar 0.709 0.293–1.716
Disease durationa 0.246 0.040–1.525
FVC 0.995 0.976–1.015
Base ? SNIP Age 0.999 0.960–1.040
Sex Males vs. females 1.009 0.406–2.505
BMI 1.064 0.963–1.175
Charlson Comorbidity Index 0.778 0.522–1.159
ALSFSr 0.970 0.915–1.029
Site of onset Spinal vs. bulbar 0.562 0.224–1.411
Disease durationa 0.355 0.055–2.300
FVC 1.001 0.980–1.021
SNIP (continuous) 0.977 0.956–0.999
The ‘‘Base’’ model included: age, sex, body mass index (BMI), Charlson Comorbidity index, Amyotrophic Lateral Sclerosis Functional Rating Scale revisited (ALSFSr), forced vital capacity (FVC), site of onset, disease duration, whereas ‘‘Base ? SNIP’’ model further included the sniff nasal inspiratory pressure (SNIP) variable as new predictor. Risks are reported as hazard ratios (HR) along with their 95 % confidence interval (95 % CI)
a Estimated HR for each unitary increase of 5 years in disease duration
Table 4Discrimination and reclassification measures for event risk prediction in amyotrophic lateral sclerosis patients adding the continuous and the categorical RECursive Partitioning and
AMalgamation (RECPAM) tree-structured sniff nasal inspiratory pressure (SNIP) variable into the clinical-based model, within 1 year of follow-up
Model Survival c-statistic (95 % CI)
Survival c-statistic difference (p value) Model’s calibration (p value) cNRI cNRI-events cNRI-non-events p value Basea 0.839 (0.708–0.971) 0.069 0.977 0.582 0.310 0.272 0.036 Base ? SNIP (cont)b 0.907 (0.850–0.963) 0.996 Base ? SNIP (tree-str)c 0.911 (0.847–0.974) 0.062 0.903 0.771 0.352 0.419 0.009
Charlson Comorbidity Index both in Base and Base ? SNIP models was considered as categorical variable
a Base: clinical-based multivariate model which included: age, sex, body mass index, Charlson Comorbidity Index, Amyotrophic Lateral Sclerosis Functional Rating Scale revisited, forced vital capacity, site of onset, disease duration
b Base ? SNIP (cont): clinical-based multivariate model which further included the continuous SNIP variable
c Base ? SNIP (tree-str): clinical-based multivariate model which further included the tree-structured SNIP categorical variable, with categories defined from results of RECPAM analysis. SNIP was categorized into the following three classes: Class 1: SNIP B18 cmH2O; Class 2: 18 \ SNIP B51 cmH2O; Class 3: SNIP [51 cmH2O
better discriminate events from non-events (within 1 year of follow-up) than the continuous SNIP (c-statistic: 0.91, 95 % CI 0.85–0.97) and correctly reclassified the risk of the composite events in the 35.1 % of events and in the 41.9 % of non-events, respectively, achieving a cNRI of 0.77 (p = 0.009) which was greater than cNRI obtained with continuous SNIP. The second RECPAM tree-struc-tured analysis, where SNIP was introduced as determinant variable, did not detect any subgroups of patients for which SNIP had a heterogeneous effect (data not shown).
Finally, using only ALS patients with spinal onset of the disease, both univariate (Table5) and multivariate (Table6) Cox models showed results mostly overlapping with those reported in the models including the whole sample. Noteworthy, comparing ‘‘Base ± SNIP’’ (cate-gorical tree-structured) vs. ‘‘Base’’ models, even though a
non-significant increase in survival c-statistics (SurvC) have been found (from SurvC = 0.905 to SurvC = 0.907, p = 0.391), a significant cNRI have been achieved (cNRI = 0.653, 95 % CI: -0.090, 1.398, p = 0.042), thus confirming that SNIP was still of greater value over FVC.
Discussion
In the present observational study, we showed that SNIP measured at baseline identified ALS patients with early respiratory dysfunction, being a good prognostic indicator of tracheostomy or death within 1 year of follow-up. The optimal cut-off for SNIP was 34 cmH2O and the
optimal-estimated cut-off for FVC was 75.9 % of predicted value with higher sensitivity and specificity for SNIP compared
Fig. 2 Identification of subgroups of patients with amyotrophic lateral sclerosis (ALS) at different risks for the composite event (tracheotomy or death): results of RECursive Partitioning and AMalgamation (RECPAM) analysis. Figure shows ALS patients with different risks of tracheotomy or death occurrences, based on combinations of key clinical characteristics that were identified by the REPCAM analysis. The tree-growing algorithm estimates hazard ratios from a Cox proportional hazards regression model with sex, Amyotrophic Lateral Sclerosis Functional Rating Scale revisited (ALSFSr), site of the onset, forced vital capacity (FVC), and sniff nasal inspiratory pressure (SNIP) as candidate splitting variables. Age at the first visit, Charlson Comorbidity Index (CCI), and disease duration (for each unitary increase of 5 years) were used as global adjustment variables. Chosen splitting variables are shown between branches, while condition sending patients to left or right sibling is on relative branch. Results were reported as hazard ratios (HR) along with their 95 % confidence interval (95 % CI). Class 3 with the
lowest event rate was reference category (HR = 1). Circles indicate subgroups of patients. Squares indicate patient subgroup RECPAM class. Numbers inside circles and squares represent the number of events (top) and the number of non-events (bottom), respectively. RECPAM results: SNIP was the only and the most important variable for differentiating all risk categories, whereas sex, ALSFSr, site of the onset, and FVC resulted irrelevant for identification of further prognostic classes. SNIP greater than 51 cmH2O identified the reference class (HR = 1), whereas SNIP lower than or equal to 18 cmH2O identified the class with the highest risk for composite event (Class 1, HR = 9.85, 95 %CI: 2.67–36.29, p \ 0.001). Fur-thermore, SNIP values greater than 18 and lower or equal to 51 cmH2O identified the intermediate risk class (Class 2, HR = 3.53, 95 %CI: 1.14–10.91, p = 0.028). Moreover, although none of the global variables were statistically associated to the composite event, a slight statistical association with the composite event was suggested by CCI (HR = 0.73, 95 %CI: 0.49–1.09, p = 0.121)
to FVC. ALS patients with SNIP and FVC at baseline lower than the respective cut-off values were classified as likely to develop tracheostomy or death at one-year
follow-up. However, the overall discriminatory power for SNIP was higher than FVC (AUC = 0.80 vs. AUC = 0.57). RECPAM analysis identified also sub-groups of patients at different risk for the composite event (tracheostomy/death) and SNIP was the only and the most important variable for differentiating all risk categories, whereas sex, ALSFSr, site of onset, and FVC were irrele-vant for identification of further prognostic classes. Finally, using only ALS patients with spinal onset of the disease, our findings were mostly overlapping with those reported in the models including the whole sample, thus confirming that SNIP was still of greater value over FVC also in this sub-sample.
Population-based studies suggested that bulbar onset disease may be associated with a worse prognosis than spinal onset [4, 24]. In the present study, site of onset appeared not to be a prognostic factor, as also reported in a recent study according to which the site of onset did not influence the risk of early death within 12 months from first diagnosis in ALS patients [25]. However, although not statistically significant, the present findings suggested a better prognosis for subjects with spinal onset of disease. In our cohort, respiratory muscle strength was clearly reduced in ALS patients who still had a normal FVC, according to previous findings indicating impairment of inspiratory muscles [26]. Patients with lower SNIP values at baseline may have a greater benefit from early diagnosis of respi-ratory dysfunction so clinicians can prompt timely NIV, known to prolong survival in ALS [27]. A positive corre-lation was recorded between FVC and SNIP values, as found in other studies [28]. SNIP was reported to be the most reliable respiratory test in ALS, combining linear decline, good sensitivity, and high reproducibility in early and advanced stage of the disease [9]. Morgan and col-leagues also highlighted the role as predictors of mortality in ALS for both SNIP and FVC prospectively recorded at any point of follow-up [16]. In the present study, SNIP at baseline was significantly associated with the risk of death or tracheostomy in ALS patients, while FVC was not associated with the risk of this composite event. SNIP may be a better marker of respiratory muscle strength in ALS compared to FVC, as it could be performed by patients with advanced disease, providing good prognostic infor-mation [16]. In fact, FVC cannot be obtained in about 20 % of the subjects at the later stages of the disease and it was not sensitive to minimal changes in respiratory muscle strength. Nevertheless, FVC is the most commonly applied respiratory parameter and is one of the outcomes measured in ALS clinical trials. Alternative respiratory tests such as maximal inspiratory pressure and maximal expiratory pressure are more sensitive of respiratory muscle weakness than FVC, and have been significantly associated with survival in ALS [15, 29]. These tests are difficult to be Fig. 3 Adjusted survival curves of patients with amyotrophic lateral
sclerosis with respect to each identified RECursive Partitioning and AMalgamation (RECPAM) class (i.e., Class 1: SNIP B18 cmH2O; Class 2: 18 \ SNIP B 51 cmH2O; Class 3: SNIP [51 cmH2O). RECPAM classes were defined as high, medium and low risk for Classes 1, 2, and 3, respectively
Table 5 Univariate Cox regression models for amyotrophic lateral sclerosis patients with spinal onset of the disease
Variable Category HR 95 % CI Age 1.034 0.985–1.085 Sex Males vs. females 1.309 0.483–3.550 BMI 1.069 0.943–1.213 Charlson Comorbidity Index 1.194 0.796–1.790 ALSFRSr 0.942 0.884–1.004 Disease durationa 0.187 0.018–1.996 FVC 0.986 0.967–1.006 SNIP (categorical)b 1.510 1.067–2.139 SNIP (continuous) 0.969 0.946–0.992 Risks are reported as hazard ratios (HR) along with their 95 % con-fidence interval (95 % CI)
BMI body mass index, ALSFRSr Amyotrophic Lateral Sclerosis Functional Rating Scale revisited, SNIP sniff nasal inspiratory pres-sure, FVC forced vital capacity
a Estimated HR for each unitary increase of 5 years in disease duration
b Estimated HR for each unitary increment in SNIP category [i.e., \30 vs. (30–40), (30–40) vs. (40–50), (40–50) vs. (50–70) and (50–70) vs. C70]
conducted when the bulbar muscles are affected [30], as severe bulbar patients may have upper airway dysfunction, experiencing difficulty in inserting or catching the mouth-piece [31]. SNIP is a short, reliable, voluntary inspiratory maneuver, simple to perform even in severe and bulbar ALS [14], correlating well with invasive and non-volitional tests of diaphragm strength in ALS [13]. SNIP does not require a mouthpiece and involves a natural manoeuver. Indeed, measurements were made at functional residual capacity from end expiratory lung volume with the patients seated comfortably. SNIP is known to predict hypoventi-lation and hypercapnia with a greater sensitivity than FVC [9, 13], and this test may be a reliable clinical tool to predict also early nocturnal sleep disorders in ALS patients [32].
Previous studies investigated SNIP to predict mortality through the categorization of SNIP measurement into units of 10 cmH2O below 50 cmH2O, with a SNIP \40 cmH2O
that was 97 % sensitive for death at 6 months [16]. In a Caucasian population of healthy subjects between 20 and
80 years, SNIP mean values were 91–117 cmH2O for men
and 75.5–94 cmH2O for women [33]. In the ATS/ERS
statement on respiratory muscle testing, SNIP values [60 cmH2O in women and [70 cmH2O in men were
unli-kely associated with significant respiratory dysfunction [22]. In the present study, we stratified the risk of death/trache-ostomy according to different SNIP levels [16], adjusted for global variables. Two multivariate prediction models have been implemented to evaluate the contribution provided by SNIP in terms of prediction ability, which was assessed both with standard methods (differences in c-statistics) and with the new reclassification measures [23]. Furthermore, with a sophisticated tree-growing technique, we identified different subgroups of patients at different risk for the events trache-ostomy/death. A SNIP cutoff value [51 cmH2O identified
the group of ALS patients with the lowest risk, whereas a SNIP cutoff value B18 cmH2O identified the group with the
highest risk to experience the composite event.
A potential limitation of the present study may be rep-resented by the lack of evaluation of SNIP during the follow-Table 6 Multivariate Cox
regression models for amyotrophic lateral sclerosis patients with spinal onset of the disease without and with sniff nasal inspiratory pressure (SNIP), both as continuous variable (i.e., Model ‘‘Base’’ and ‘‘Base ± SNIP’’, respectively) and SNIP as categorical variable (i.e., ‘‘Base ± SNIP categorical tree-structured’’), where SNIP categories were found using RECursive Partitioning and AMalgamation (RECPAM) algorithm. Risks are reported as hazard ratios (HR) along with their 95 % confidence interval (95 % CI)
BMI body mass index, ALSFSr Amyotrophic Lateral Sclerosis Functional Rating Scale revisited, FVC forced vital capacity
a Estimated HR for each unitary increase of 5 years in disease duration
Model Variable Category HR 95 % CI
Base Age 1.013 0.961–1.067 Sex Males vs. females 0.831 0.281–2.461 BMI 1.129 1.000–1.275 Charlson Comorbidity Index 1.207 0.782–1.864 ALSFSr 0.927 0.849–1.012 Disease durationa 0.280 0.026–2.988 FVC 0.996 0.971–1.022
Base ? SNIP (continuous) Age 1.005 0.957–1.054
Sex Males vs. females 1.028 0.330–3.204 BMI 1.110 0.987–1.248 Charlson Comorbidity Index 1.236 0.778–1.964 ALSFSr 0.958 0.875–1.050 Disease durationa 0.562 0.055–5.754 FVC 1.002 0.976–1.029 SNIP (continuous) 0.973 0.943–1.003 Base ? SNIP (categorical
tree-structured) Age 0.993 0.941–1.047 Sex Males vs. females 1.156 0.355–3.762 BMI 1.106 0.985–1.242 Charlson Comorbidity Index 1.137 0.709–1.824 ALSFSr 0.970 0.886–1.062 Disease durationa 0.551 0.046–6.551 FVC 0.998 0.972–1.024 SNIP: B18 vs. [51 10.085 1.397–72.813 SNIP: (18–51) vs. [51 3.732 0.711–19.595
up. Another limitation may be that the study was conducted in a tertiary care center. In fact, the selection may be a further limitation because patients with older age and bulbar onset are less likely to be referred to a tertiary center of care. In fact, there is a general consensus that older age and bulbar onset are negatively related to ALS outcome [4], and it has been also suggested that patients enrolled in clinical trials from tertiary care centers included younger subjects with a better prognosis [34]. In this study, we evaluated the prog-nostic role of a respiratory test in ALS patients with REC-PAM analysis, already used to study several prognostic factors in patients with lung cancer [35]. Furthermore, the statistical value of this model has been supported by the use of the survival-based cNRI. The addition of SNIP as cate-gories, identified and validated by RECPAM analysis, gave a more significant contribute to improve the discriminatory power of model and the reclassification of the risk, respec-tively, in the events and non-events (cNRI) when compared with SNIP as continuous value.
The present results showed that SNIP is a good prog-nostic indicator in ALS. Although many years have passed since SNIP has been described for the first time as a viable measure of respiratory muscle strength [12], it is not well known how widespread its application is in clinical prac-tice. To the best of our knowledge, SNIP is used to assess respiratory function primarily in tertiary care centers for ALS, as also suggested by the recent guidelines of the EFNS Task Force on Diagnosis and Management of ALS proposing SNIP as a decisional parameter for beginning NIV (SNIP B40 cmH2O) [36]. The present findings may
have several consequences in the multidisciplinary man-agement and planning of symptomatic care of these patients. The evaluation of SNIP in the early phase of ALS may contribute to identify patients with high risk of mor-tality or intubation. SNIP provides an additional tool for baseline stratification of patients in clinical trials. The early identification of respiratory dysfunction in ALS patients and its prompt and proper treatment could reduce hospi-talizations, with important policy implications and reduc-tion of the burden that ALS patients may pose on the National Health Service and healthcare systems worldwide. Acknowledgments This research was supported by European Community’s Seventh Framework Programme (FP7/2007-2013 under grant agreement 259867).
Conflicts of interest The authors declare no financial or other conflicts of interest.
Ethical standard The study has been approved by the Local Ethical Committee and has therefore been performed in accordance with the ethical standards laid down World Medical Association’s 2008 Declaration of Helsinki. All persons gave their informed consent prior to their inclusion in the study.
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