Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 273-283 |
| Number of pages | 11 |
| Journal | Clinical Otolaryngology |
| Volume | 46 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 2021 |
Keywords
- conservative management
- diagnosis
- follow-up
- growth
- history
- prediction model
- quality-of-life
- risk
- size
- tumor-growth
- vestibular schwannoma
- wait and scan
- DIAGNOSIS
- SIZE
- FOLLOW-UP
- RISK
- QUALITY-OF-LIFE
- CONSERVATIVE MANAGEMENT
- TUMOR-GROWTH
- HISTORY
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- 10.1111/coa.13661Licence: CC BY
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In: Clinical Otolaryngology, Vol. 46, No. 1, 01.01.2021, p. 273-283.
Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Development of a model to predict vestibular schwannoma growth: An opportunity to introduce new wait and scan strategies
AU - Hentschel, M.A.
AU - Hannink, G.
AU - Steens, S.C.A.
AU - Mulder, J.J.S.
AU - Rovers, M.M.
AU - Kunst, H.P.M.
N1 - Funding Information: We developed a multivariable prediction model to predict VS growth. Information on potential predictors and the outcome was retrospectively collected from patient records. The study protocol was published online (in Dutch, summary in English: https://www.zonmw.nl/nl/onderzoek-resultaten/doelmatigheidsonderzoek/programmas/project-detail/doelmatigheidsonderzoek/cost-effective-diagnostic-strategies-in-patients-with-asymmetrical-hearing-impairment-or-unilateral/verslagen/). The study was reported following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement.8 Most patients with a newly diagnosed VS are referred to a specialised tertiary centre to determine further management. We consulted medical records of all patients that got assigned the diagnostic code ?cerebellopontine angle (CPA) lesion? and/or had undergone an MRI of the CPA in a tertiary hospital between 1990 and July 2016. We identified patients with a unilateral VS diagnosed by means of MRI. All patients initially assigned to a W&S strategy were included. The local W&S strategy prescribes MRIs at 1, 2, 3, 5, 7, 9, 12 and 15?years following diagnosis, then continuing every 5?years during the remaining lifetime of a patient. The W&S strategy could either be carried out in our own institution or in the referring clinic. To be able to study VS growth at least one follow-up MRI (either images or a report) had to be available. Thus, patients diagnosed with other modalities than MRI, those with bilateral VSs (ie neurofibromatosis), VSs that immediately had been treated, or without available follow-up, or CPA lesions other than VS were excluded. Time-to-VS growth was defined as the number of months between the baseline MRI and the one on which VS growth was detected. MRI examinations were assessed by one of the authors [MH] to determine whether growth had occurred. Each MRI was compared to the baseline MRI. Largest VS diameter was measured in two directions on axial images, that is parallel to the internal auditory canal (split in an intra- and extrameatal portion delineated by the petrous bone)9 and largest extrameatal diameter parallel to the petrous bone. All measurements were rounded off to millimetres. Contrast enhanced T1-weighted images were preferably used to assess lesions. In case these were unavailable, T2-weighted images were used. For intrameatal VSs, an increase in tumour diameter ?2?mm parallel to the internal auditory canal was considered growth. For extrameatal VSs, growth was considered an increase ?2?mm of the extrameatal portion in either direction.9 Whenever the W&S strategy was performed in another hospital and baseline or follow-up MRI images were unavailable, we evaluated growth based on the radiologists? reports. When the report stated that growth had occurred, we assumed this to be true. Twenty-two potential predictors were selected based on literature and interviews with three experts (otolaryngologists from our centre, working in the field of VS). Demographics (sex [male/female] and age), symptoms, pure-tone audiometry (PTA) and MRI findings at time of diagnosis were collected from the patients? medical records. Presence of complaints of hearing loss, tinnitus and aural pressure on the affected side were collected [yes/no]. The onset of hearing loss was classified [sudden/gradual]. Also, the presence of vertigo or balance complaints was collected [present/absent]. The time since onset of symptoms up to diagnosis was expressed in months [continuous variable]. PTA data were retrieved from the clinical audiology database system AudiologicX (version 1.0.6, MarYor, the Netherlands). In our centre, PTA is performed in a soundproof room according to standard audiometric protocols. We collected hearing thresholds in dB hearing loss of octave frequencies 0.5, 1, 2, 4 and 8?kHz for air conduction (AC). Measurements on the affected side were used. Results of PTA performed within a range of six?months prior and after diagnosis were included. In case a patient had multiple PTA examinations available, the one most proximate to the diagnostic MRI was selected. Baseline MRI images were assessed to determine VS size [continuous variable, in mm] as previously described, aspect [homogeneous/inhomogeneous], presence of cysts within the inhomogeneous VSs [yes/no] and Koos grading scale [grade 1-4], representing the lesion's size in relation to surrounding structures.10 Descriptive statistics were used to summarise the data. For 15 of the 22 potential predictors, data were missing, ranging between 2.2% and 63.8% (Table?1). We assumed missing data to be missing at random (MAR). Imputation of missing values was performed using multiple imputation by chained equations, creating 25 imputation sets.11 Potential predictors were entered into a Cox regression model, taking into account the multiple imputed data sets. Akaike's information criterion was used as a selection criterion.12 The probability of VS growth at a certain time point can be calculated by using the following formula: 1???S(t), where S(t)?=?S0(t)^exp (?1x1?+??2x2?+..?+??nxn). In this formula, S(t) is the ?survival? of VS, that is the probability of no VS growth. S0(t) represents the baseline survival at time t, and ?1, ?2 and ?n are the regression coefficients of the predictors x1, x2 and xn, respectively, after having been pooled. Baseline survival is defined as the survival for the mean of all covariates in the model and can be transformed into a probability of future growth at the different time points for an individual patient. For newly diagnosed VS patients assigned to a W&S strategy, predictions within the first five years following diagnosis are of interest to determine timing of the first follow-up MRI. Predictions at ten years are relevant for a patient's prognosis. Model performance was assessed on calibration using calibration plots for predictions at 1-5 and 10?years. The model's ability to discriminate between patients with successful or unsuccessful outcomes was estimated using Harrell's C.13 Prediction models derived with multivariable regression analyses are known for overfitting. This results in too extreme predictions when the model is applied in new cases. Therefore, it was validated internally using bootstrapping techniques. Five hundred samples were drawn with replacement from the development sample. Bootstrapping techniques provide information on the performance of the model in comparable datasets and generate a shrinkage factor to adjust regression coefficients.14 Thereafter, model performance was re-evaluated. For development of multivariable prediction models, sample size is often based on the number of events per parameter estimated (EPP). This can be calculated by dividing the number of individuals with or without the outcome (whichever is lower) by the number of parameters to be estimated. We used 22 potential predictors that make up 24 parameters to be estimated (including multiple categories of the variable ?Koos grade?), amounting to an EPP of 23 (EPP?=?564 ?events [no VS growth]? divided by 24 parameters to be estimated). An EPP above 20 is considered to eliminate the estimated bias in regression coefficients and achieve reliable results.15,16 A dynamic nomogram was created to easily calculate an individual's risk of VS growth. The nomogram is available via https://vs-model.shinyapps.io/predictVSgrowth, where more data can be entered and corresponding predictions on VS growth can be calculated. TRIPOD recommends to evaluate netbenefit of prediction models.16 Decision curve analysis (DCA) can help to summarise clinical usefulness of prediction models and support in decision making.17,18 In a DCA, netbenefit is plotted against threshold probability. In this study, netbenefit represents the proportion of true positives (detected VS growth) in absence of any false positives (ie specificity of 100%).18 Threshold probability is defined as the minimum predicted risk of VS growth at which an otolaryngologist or patient would want the first follow-up MRI. A range of values for the threshold probability is displayed in order to represent a variation in preferences.19,20 Interviews with experts in the field of VS revealed a relevant range of risk threshold values of 10% (MRI in 10 patients to detect one case of VS growth and accept 9 false positives, ie unnecessary MRIs) to 30% (MRI in 10 patients to detect 3 cases of growth and accept 7 false positives). DCA was performed for the different time points (1-5 and 10?years). These can be used to compare the model to a ?scan all? (ie the current), and ?scan none? strategy and enable one to determine the threshold probability to initiate follow-up. Furthermore, we calculated the number of MRIs avoided for different threshold probabilities for each of the first five years. Data analysis was performed in R version 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria) using packages ?rms? and ?rmda".21,22 This study was performed with consent of the local medical ethics committee. The need for informed consent was waived, because of the retrospective nature and size of the study. Publisher Copyright: © 2020 The Authors. Clinical Otolaryngology published by John Wiley & Sons Ltd.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - Objectives To develop a prediction model to predict vestibular schwannoma (VS) growth for patients in a wait and scan (W&S) strategy.Design Retrospective cohort study.Setting Tertiary hospital (Radboud university medical center, Nijmegen, the Netherlands).Participants Patients with unilateral VS, entering a W&S strategy and at least one follow-up MRI available. Data on demographics, symptoms, audiometry and MRI characteristics at time of diagnosis were collected from medical records.Main outcome measures Following multiple imputation, a multivariable Cox regression model was used to select variables, using VS growth (>= 2 mm) as outcome. Decision curve analyses (DCA) were performed to compare the model to the current strategy.Results Of 1217 analysed VS patients, 653 (53.7%) showed growth during follow-up. Balance complaints (HR 1.57 (95% CI: 1.31-1.88)) and tinnitus complaints in the affected ear (HR 1.36 (95% CI: 1.15-1.61)), Koos grade (Koos 1 is reference, Koos 2 HR 1.03 (95% CI: 0.80-1.31), Koos 3 HR 1.55 (95% CI: 1.16-2.06), Koos 4 HR 2.18 (95% CI: 1.60-2.96)), time since onset of symptoms (IQR HR 0.83 (95% CI: 0.77-0.88) and intrameatal diameter on MRI (IQR HR 1.67 (95% CI: 1.42-1.96)) were selected as significant predictors. The model's discrimination (Harrell's C) was 0.69 (95% CI: 0.67-0.71), and calibration was good. DCA showed that the model has a higher net benefit than the current strategy for probabilities of VS growth of >12%, 15% and 21% for the first consecutive 3 years, respectively.Conclusions Patients with balance and tinnitus complaints, a higher Koos grade, short duration of symptoms and a larger intrameatal diameter at time of diagnosis have a higher probability of future VS growth. After external validation, this model may be used to inform patients about their prognosis, individualise the W&S strategy and improve (cost-)effectiveness.
AB - Objectives To develop a prediction model to predict vestibular schwannoma (VS) growth for patients in a wait and scan (W&S) strategy.Design Retrospective cohort study.Setting Tertiary hospital (Radboud university medical center, Nijmegen, the Netherlands).Participants Patients with unilateral VS, entering a W&S strategy and at least one follow-up MRI available. Data on demographics, symptoms, audiometry and MRI characteristics at time of diagnosis were collected from medical records.Main outcome measures Following multiple imputation, a multivariable Cox regression model was used to select variables, using VS growth (>= 2 mm) as outcome. Decision curve analyses (DCA) were performed to compare the model to the current strategy.Results Of 1217 analysed VS patients, 653 (53.7%) showed growth during follow-up. Balance complaints (HR 1.57 (95% CI: 1.31-1.88)) and tinnitus complaints in the affected ear (HR 1.36 (95% CI: 1.15-1.61)), Koos grade (Koos 1 is reference, Koos 2 HR 1.03 (95% CI: 0.80-1.31), Koos 3 HR 1.55 (95% CI: 1.16-2.06), Koos 4 HR 2.18 (95% CI: 1.60-2.96)), time since onset of symptoms (IQR HR 0.83 (95% CI: 0.77-0.88) and intrameatal diameter on MRI (IQR HR 1.67 (95% CI: 1.42-1.96)) were selected as significant predictors. The model's discrimination (Harrell's C) was 0.69 (95% CI: 0.67-0.71), and calibration was good. DCA showed that the model has a higher net benefit than the current strategy for probabilities of VS growth of >12%, 15% and 21% for the first consecutive 3 years, respectively.Conclusions Patients with balance and tinnitus complaints, a higher Koos grade, short duration of symptoms and a larger intrameatal diameter at time of diagnosis have a higher probability of future VS growth. After external validation, this model may be used to inform patients about their prognosis, individualise the W&S strategy and improve (cost-)effectiveness.
KW - conservative management
KW - diagnosis
KW - follow-up
KW - growth
KW - history
KW - prediction model
KW - quality-of-life
KW - risk
KW - size
KW - tumor-growth
KW - vestibular schwannoma
KW - wait and scan
KW - DIAGNOSIS
KW - SIZE
KW - FOLLOW-UP
KW - RISK
KW - QUALITY-OF-LIFE
KW - CONSERVATIVE MANAGEMENT
KW - TUMOR-GROWTH
KW - HISTORY
U2 - 10.1111/coa.13661
DO - 10.1111/coa.13661
M3 - Article
C2 - 33090707
SN - 1749-4478
VL - 46
SP - 273
EP - 283
JO - Clinical Otolaryngology
JF - Clinical Otolaryngology
IS - 1
ER -