CBSF markdown
2026-02-17
1 Overall Summary
The CBSF total score and subscores are reliable, even in participants with baseline impairments (Rho, ICC). The individual items vary in reliability, but most are reliable. Stable controls are the least reliable, though this is largely due to 0s on most baseline items.
Validity established through strong correlations between the CBSF and the UPDRS, PSPRS, and MIR. Validity further demonstrated via strong associations between items on the CBSF and related items on other tasks. The CBSF also differentiates groups in the expected pattern (e.g., impaired > controls; CBS/PSP > AD). AUCs are strong for CBSF as well (e.g., CBS/PSP vs svPPA: AUC=.90). Within a diagnostic group (e.g., CBS), those who are more impaired have higher CBSF scores. CBSF differentiates mutation+ asymptomatics from mutation+ presymptomatics.
Longitudinally, CBSF predicts change in MIR and FTLD CDR, while controlling for baseline MIR or FTLD CDR. I have not looked at CBSF predicting conversion.
Change over 2 visits is shown in plots and split by baseline diagnosis. Participants retain the diagnosis at both time points. The CBSF performs as expected; e.g., greatest change in total score seen by PSP.
For clinical trials, the sample required to detect a significant change on the CBSF is smaller or about equal to other variables (FTLD CDR sbs, UPDRS, PSPRS, MoCA etc.)2 Table One
- Table one: We have ~ 1200 people with at least 1 CBSF completed. Table one shows these participants split by broad diagnosis categories. Let me know if you want the DX groups set up differently. It’s an easy fix. I also categorized FLTD CDR global scores into 0, 0.5, and 1+.
3 Test Retest
Here we’re looking at reliability via Spearman Rho and ICCs. I first look at the full sample, then at various subsamples. I limited the retest interval to ~1 year, with the exception of the unimpaired group, which I pushed out to two years. Briefly, the summary measures are moderately reliable or above. This is even true for folks who have symptoms at baseline and do not change in clinical severity over time. The individual items are less reliable, which is typical of scales. All groups have the same limits at both time points (e.g., baseline FTLD CDR= 0.5 group is 0.5 at both visits). The tables are ordered by Spearman Rho, with the first row being the largest Spearman Rho; in general, this is the Total score, Motor score, or Non-motor score. Full sample: the summary scores are all moderately reliable or above (> .75). Many of the individual items are also reliable. I imagine the reliability of individual items varies based on subgroup. Controls: These are diagnoses as unimpaired and/or have a global score of 0. They are mutation negative. This is our least reliable group, although the total score and language/behavior/cog summary score are still > .60. The issue here is that many of the items have are 0 at both time points (designated by *). FTLD CDR >= 0.5 Moderate of above reliability for all summary scores. Other I also looked at a few other subsamples here and can report on them if you’d like (e.g., CBS +PSP at baseline).
3.1 Full Sample
We also have plots for each item on the CBSF.
3.2 Control: Global=0; DX=CU, Mutation negative
3.3 Baseline FTLD CDR >= 0.5
4 Cross sectional
4.1 Heatmap Summary
Summary: simple correlations between the CBSF total score and some other scores. Demonstrates convergent validity quite well (e.g., r=.66 with CBSF and PSPRS). The first heatmap shows total scores primarily.
The remaining heatmaps include all components of the CBSF and are very hard to read. The information in those figures is also provided in table. The goal here was to show that items on the CBSF were related to similar items on other measures. For example, CBSF walking impairment is associated with PSPRS Falls (.77), Gait (.75), and Arising (.71). 
4.2 Heatmap PSPRS
Showing correlations between PSPRS and CBSF across all items.This is not for the paper. Point here is to look at general pattern of results. Hard to read, point is that the items on the PSPRS are highly correlated with like items on the CBSF, You can save the image to look at it more closely. Alternatively there is the correlation table below.
4.3 Heatmap UPDRS
Same as above, but with UPDRS
4.4 Presymptomatic and Mild Symptoms
Here I compare CBSF total score between Asymptomatic (FTLD CDR-g=0; Mut+) and Presymptomatic (FTLD CDR-g=0.5, Mut+). We see a significant difference between groups.
I then look at each subscores and we see that the difference between groups is weakest on the motor subscore. Controls for age, sex
## [1] "Mann-Whitney U test also signifiacnt."##
## Wilcoxon rank sum test with continuity correction
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## data: CBS_TOTAL_SCORE by cntvspre
## W = 1657.5, p-value = 9.964e-09
## alternative hypothesis: true location shift is not equal to 0##
## Wilcoxon rank sum test with continuity correction
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## data: PSPRS_TOTAL by cntvspre
## W = 1955, p-value = 0.0001305
## alternative hypothesis: true location shift is not equal to 04.4.1 Total and subscores
5 Diagnosis, FTLD CDR Global score, and CBSF Scores
## $`Total score by Diagnosis`
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## $`Motor score by Diagnosis`
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## $`Non-motor score by Diagnosis`
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## $`Lang/cog/beh score by Diagnosis`
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## $Summary
6 Diagnosis and CBSF Motor Score
With several graphs, we look at how scores differ by diagnosis or ftld cdr global score.
The first few graphs shows boxplots with dots colored by FTLD CDR global score. Take away here is that, within diagnosis group, those with greater symptoms (e.g., 1+) have higher scores. Also, we see expected differences between groups: e.g., PSP > AD for total score, motor score, and nonmotor score but not the language/cognitive/behavior score.
Next few graphs look at the CBSF motor score across diagnoses, with the dots colored by a CDR-like Motor score variable. We again see that higher CBSF scores have higher Motor scores. We also again see the expected group differences. The next graph repeats this, but sums up motor items from the UPDRS/neuroexam (higher = more impairment). Same info as prior graph, but with a continuous color variable. The next is
I then look at all items on the CBSF by diagnosis, color coded by motor variables. There’s a lot here, but some key findings:
Motor items are generally worse in things like CBS and PSP vs other diagnoses.
Sleeping items seem to be worse for DLB (small sample size)
Language variables are a bit inconsistent, but we do see some nice findings: lvPPA and svPP have higher CBS_understanding scores than other groups, including nfvPPA
Cognitive: seems a bit more variable across diagnoses. Most groups endorse some on average. That said, CBSF remember is greatest in AD, svPPA, lvPPA, other cognitive, which makes sense.
Next we look at CBSF scores by diagnosis, with color coded by UPDRS motor items. Variables with “NE_” have normal =1, otherwise higher number is impaired.
Repetitive with above, but again, just another convergent validity analysis. Though we do see some expected findings: folks with higher motor scores have greater bradykinesia. The expected diagnoses have the highest motor scores and bradykinesia scores.##Color Group is MIR Motor Score
6.1 CBSF Motor Score by count of impaired motor
6.1.1 Sums all scores on neuroexam items. 0=no impaired motor at all.
6.2 CBSF item level by MIR motor score
## $CBS_MOTOR_SCORE
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## $CBS_SPEAKING
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## $CBS_INOUT
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## $CBS_WALKING
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## $CBS_SPONTMOVE
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## $CBS_SALIVA
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## $CBS_EATING
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## $CBS_CHEWING
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## $CBS_DRESSING
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## $CBS_HYGIENE
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## $CBS_HANDWRITING
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## $CBS_HOBBIES
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## $CBS_TURNINGBED
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## $CBS_LCB_SCORE
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## $CBS_UNDERSTAND
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## $CBS_ANXIOUS
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## $CBS_MOTIVATED
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## $CBS_CARING
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## $CBS_AGITATION
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## $CBS_THINKING
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## $CBS_REMEMBER
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## $CBS_FINANCE
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## $CBS_MULTITASK
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## $CBS_ACTINGAPP
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## $CBS_REPET
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## $CBS_DIETPREF
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## $CBS_MOOD
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## $CBS_NONMOTOR_SCORE
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## $CBS_SLEEPING
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## $CBS_STAYAWAKE
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## $CBS_FATIGUED
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## $CBS_URINPROB
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## $CBS_VISUALPROB
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## $CBS_FINDINGWAY
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## $CBS_TOTAL_SCORE
6.3 CBSF Motor Score by all neuroexam motor
6.3.1 note: “NE_” variables normal =1. For all others, higher number = more impaired
## $TRACTLHD
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## $TRACTRHD
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## $ARISING
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## $BRADYKIN
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## $FACEXP
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## $TAPSLF
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## $TAPSRT
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## $GAIT
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## $HANDMOVL
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## $HANDMOVR
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## $LEGLF
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## $LEGRT
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## $POSTURE
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## $POSSTAB
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## $HANDALTL
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## $HANDALTR
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## $RIGDLOLF
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## $RIGDUPLF
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## $RIGDNECK
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## $RIGDLORT
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## $RIGDUPRT
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## $SPEECH
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## $TRESTFAC
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## $TRESTLFT
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## $TRESTLHD
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## $TRESTRFT
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## $TRESTRHD
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## $MC_MOTOR
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## $NE_ENTIRE_EXAM
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## $NE_CRANIAL_NERVES
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## $NE_MOTOR
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## $NE_COORDINATION
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## $NE_REFLEXES
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## $NE_GAIT
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## $motor_0vs1
7 Longitudinal
Here I calculated change scores (visit 2 – visit 1) for several measures (e.g., UPDRS, PSPRS). I then look at how baseline CBSF scores predict this change. I first do this with a simple Rho, then I look at this comparison after accounting for baseline scores in the change metric (Rho simple). As in the association between CBSF total score and UPDRS change, while accounting for baseline UPDRS (Rho). I then show some plots.
I do the above for the CBSF total score and each of the summary scores.7.1 Prediction of change (anualized)
7.1.1 CBSF Total score
## Variable Rho P Rho.simple P.simple
## 1 UPDRS_SCORE 0.0124 0.7922 0.3928769 0
## 2 FTLDCDRM_SB 0.0853 0.1031 0.5457399 0
## 3 FTLDCDR_SB 0.1170 0.0082 0.5053321 0
## 4 MC_MOTOR -0.1128 0.0365 0.3136829 0
## 5 PSPRS_TOTAL -0.0673 0.1579 0.4024309 0## $UPDRS_SCORE## `geom_smooth()` using formula = 'y ~ x'
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## $FTLDCDRM_SB## `geom_smooth()` using formula = 'y ~ x'
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## $FTLDCDR_SB## `geom_smooth()` using formula = 'y ~ x'
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## $MC_MOTOR## `geom_smooth()` using formula = 'y ~ x'
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## $PSPRS_TOTAL## `geom_smooth()` using formula = 'y ~ x'
7.1.2 CBSF Motor Score
| Variable | Rho | P | Rho.simple | P.simple |
|---|---|---|---|---|
| UPDRS_SCORE | 0.0728 | 0.1219 | 0.5594402 | 0 |
| FTLDCDRM_SB | 0.0522 | 0.3196 | 0.4558835 | 0 |
| FTLDCDR_SB | 0.0789 | 0.0751 | 0.4097465 | 0 |
| MC_MOTOR | -0.1976 | 0.0002 | 0.3002764 | 0 |
| PSPRS_TOTAL | 0.0079 | 0.8681 | 0.4825160 | 0 |
## $UPDRS_SCORE## `geom_smooth()` using formula = 'y ~ x'
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## $FTLDCDRM_SB## `geom_smooth()` using formula = 'y ~ x'
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## $FTLDCDR_SB## `geom_smooth()` using formula = 'y ~ x'
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## $MC_MOTOR## `geom_smooth()` using formula = 'y ~ x'
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## $PSPRS_TOTAL## `geom_smooth()` using formula = 'y ~ x'
7.1.3 CBSF Nonmotor score
| Variable | Rho | P | Rho.simple | P.simple |
|---|---|---|---|---|
| UPDRS_SCORE | -0.0474 | 0.3143 | 0.2876561 | 0 |
| FTLDCDRM_SB | 0.0278 | 0.5954 | 0.3631952 | 0 |
| FTLDCDR_SB | 0.0284 | 0.5232 | 0.3147312 | 0 |
| MC_MOTOR | -0.1049 | 0.0518 | 0.2830234 | 0 |
| PSPRS_TOTAL | -0.1051 | 0.0271 | 0.2689655 | 0 |
## $UPDRS_SCORE## `geom_smooth()` using formula = 'y ~ x'
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## $FTLDCDRM_SB## `geom_smooth()` using formula = 'y ~ x'
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## $FTLDCDR_SB## `geom_smooth()` using formula = 'y ~ x'
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## $MC_MOTOR## `geom_smooth()` using formula = 'y ~ x'
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## $PSPRS_TOTAL## `geom_smooth()` using formula = 'y ~ x'
7.1.4 CBSF lang/beh/cog score
| Variable | Rho | P | Rho.simple | P.simple |
|---|---|---|---|---|
| UPDRS_SCORE | -0.0098 | 0.8350 | 0.2085230 | 0 |
| FTLDCDRM_SB | 0.0947 | 0.0703 | 0.5472971 | 0 |
| FTLDCDR_SB | 0.1241 | 0.0051 | 0.5088222 | 0 |
| MC_MOTOR | -0.0123 | 0.8209 | 0.2975770 | 0 |
| PSPRS_TOTAL | -0.1059 | 0.0259 | 0.2508235 | 0 |
## $UPDRS_SCORE## `geom_smooth()` using formula = 'y ~ x'
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## $FTLDCDRM_SB## `geom_smooth()` using formula = 'y ~ x'
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## $FTLDCDR_SB## `geom_smooth()` using formula = 'y ~ x'
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## $MC_MOTOR## `geom_smooth()` using formula = 'y ~ x'
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## $PSPRS_TOTAL## `geom_smooth()` using formula = 'y ~ x'
7.2 Sample size analyses, multiple groups
Sample size analyses: Here I calculate the necessary sample size to detect a drug effect that reduced change by 30% for several outcomes. The change is annualized: e.g., (UPDRS v2 – UPDRS v1 )/ retest_interval in years. The number of participants per arm of the study are reported in the “Estiamted_samle_per_arm” column. We have this number for the CBSF scores as well as several others. Each analysis table is sorted with the smallest necessary sample as the first column.
## ### Not_CU
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:---|:-----|:-----|:-------------|:------------|:------------------------|
## |CBS_MOTOR_SCORE |760 |1.243 |3.575 |30% reduction |0.87 |1442.038 |
## |FTLDCDR_SB |760 |0.628 |1.826 |30% reduction |0.44 |1473.559 |
## |CBS_TOTAL_SCORE |760 |2.82 |8.411 |30% reduction |1.974 |1552.018 |
## |PSPRS_TOTAL |760 |1.287 |4.647 |30% reduction |0.901 |2274.96 |
## |CBS_LCB_SCORE |760 |1.154 |4.69 |30% reduction |0.808 |2880.816 |
## |CBS_LCB_SCORE |760 |1.154 |4.69 |30% reduction |0.808 |2880.816 |
## |UPDRS_SCORE |760 |1.167 |5.07 |30% reduction |0.817 |3291.438 |
## |CBS_NONMOTOR_SCORE |760 |0.422 |2.007 |30% reduction |0.296 |3938.452 |
## ### CBSorPSPorNFVPPSorALS
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:---|:-----|:------|:-------------|:------------|:------------------------|
## |FTLDCDR_SB |199 |2.005 |2.749 |30% reduction |1.404 |327.809 |
## |CBS_MOTOR_SCORE |199 |3.809 |5.67 |30% reduction |2.666 |386.437 |
## |CBS_TOTAL_SCORE |199 |8.317 |12.448 |30% reduction |5.822 |390.786 |
## |PSPRS_TOTAL |163 |4.337 |8.166 |30% reduction |3.036 |618.213 |
## |UPDRS_SCORE |171 |4.228 |8.675 |30% reduction |2.96 |734.182 |
## |CBS_NONMOTOR_SCORE |199 |1.503 |3.219 |30% reduction |1.052 |800.604 |
## |CBS_LCB_SCORE |199 |3.005 |6.923 |30% reduction |2.104 |925.86 |
## ### CBS
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:--|:-----|:-----|:-------------|:------------|:------------------------|
## |PSPRS_TOTAL |63 |3.937 |6.569 |30% reduction |2.756 |485.765 |
## |FTLDCDR_SB |82 |1.061 |1.906 |30% reduction |0.743 |562.775 |
## |CBS_TOTAL_SCORE |82 |4.39 |8.069 |30% reduction |3.073 |589.159 |
## |CBS_MOTOR_SCORE |82 |2.5 |4.851 |30% reduction |1.75 |656.851 |
## |UPDRS_SCORE |65 |4.292 |9.156 |30% reduction |3.005 |793.669 |
## |CBS_NONMOTOR_SCORE |82 |0.854 |2.315 |30% reduction |0.598 |1283.144 |
## |CBS_LCB_SCORE |82 |1.037 |4.62 |30% reduction |0.726 |3464.714 |
## ### PSP
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:--|:-----|:------|:-------------|:------------|:------------------------|
## |CBS_MOTOR_SCORE |81 |2.963 |5.154 |30% reduction |2.074 |527.702 |
## |CBS_TOTAL_SCORE |81 |5.877 |11.641 |30% reduction |4.114 |684.418 |
## |FTLDCDR_SB |81 |0.969 |2.011 |30% reduction |0.678 |751.35 |
## |CBS_NONMOTOR_SCORE |81 |1.272 |2.651 |30% reduction |0.89 |757.803 |
## |PSPRS_TOTAL |62 |3.629 |9.302 |30% reduction |2.54 |1146.018 |
## |UPDRS_SCORE |67 |3.104 |8.514 |30% reduction |2.173 |1311.867 |
## |CBS_LCB_SCORE |81 |1.642 |5.771 |30% reduction |1.149 |2154.799 |
## ### bvFTD
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:---|:-----|:------|:-------------|:------------|:------------------------|
## |FTLDCDR_SB |156 |1.196 |2.668 |30% reduction |0.837 |868.647 |
## |CBS_TOTAL_SCORE |156 |3.891 |10.319 |30% reduction |2.724 |1226.597 |
## |CBS_MOTOR_SCORE |156 |1.314 |4.054 |30% reduction |0.92 |1660.113 |
## |CBS_LCB_SCORE |156 |1.782 |5.626 |30% reduction |1.247 |1738.613 |
## |CBS_NONMOTOR_SCORE |156 |0.795 |2.639 |30% reduction |0.556 |1922.499 |
## |PSPRS_TOTAL |136 |0.934 |4.307 |30% reduction |0.654 |3710.532 |
## |UPDRS_SCORE |142 |0.739 |3.756 |30% reduction |0.518 |4500.775 |
## ### nfvPPA
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:--|:-----|:-----|:-------------|:------------|:------------------------|
## |FTLDCDR_SB |81 |0.605 |1.457 |30% reduction |0.423 |1011.973 |
## |UPDRS_SCORE |73 |1.877 |4.622 |30% reduction |1.314 |1057.773 |
## |CBS_MOTOR_SCORE |81 |1.321 |3.643 |30% reduction |0.925 |1326.45 |
## |PSPRS_TOTAL |69 |1.464 |4.381 |30% reduction |1.025 |1562.447 |
## |CBS_TOTAL_SCORE |81 |2.42 |8.263 |30% reduction |1.694 |2033.729 |
## |CBS_LCB_SCORE |81 |0.975 |4.301 |30% reduction |0.683 |3392.097 |
## |CBS_NONMOTOR_SCORE |81 |0.123 |1.661 |30% reduction |0.086 |31579.575 |
## ### CU
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:---|:------|:-----|:-------------|:------------|:------------------------|
## |FTLDCDR_SB |432 |0.023 |0.185 |30% reduction |0.016 |11153.786 |
## |CBS_LCB_SCORE |432 |-0.127 |1.409 |30% reduction |-0.089 |21371.381 |
## |CBS_TOTAL_SCORE |432 |-0.162 |2.297 |30% reduction |-0.113 |35059.466 |
## |CBS_NONMOTOR_SCORE |432 |-0.035 |0.922 |30% reduction |-0.024 |123013.325 |
## |UPDRS_SCORE |409 |0.012 |0.521 |30% reduction |0.009 |317340.399 |
## |PSPRS_TOTAL |401 |-0.01 |0.652 |30% reduction |-0.007 |744819.279 |
## |CBS_MOTOR_SCORE |432 |0 |0.743 |30% reduction |0 |Inf |
## ### PSPorCBS
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:---|:-----|:------|:-------------|:------------|:------------------------|
## |CBS_MOTOR_SCORE |162 |2.747 |5.005 |30% reduction |1.923 |578.985 |
## |FTLDCDR_SB |162 |1.022 |1.958 |30% reduction |0.715 |640.636 |
## |CBS_TOTAL_SCORE |162 |5.16 |10.024 |30% reduction |3.612 |658.123 |
## |PSPRS_TOTAL |124 |3.815 |8.036 |30% reduction |2.67 |774.072 |
## |CBS_NONMOTOR_SCORE |162 |1.068 |2.495 |30% reduction |0.748 |952.104 |
## |UPDRS_SCORE |131 |3.718 |8.85 |30% reduction |2.602 |988.537 |
## |CBS_LCB_SCORE |162 |1.346 |5.232 |30% reduction |0.942 |2636.296 |
## ### CBSorbvFTDornfvPPAorPSP
##
##
## |Variable |N |Mean |SD |Drug_effect |Treated_Mean |Estimated_Sample_Per_Arm |
## |:------------------|:---|:-----|:-----|:-------------|:------------|:------------------------|
## |FTLDCDR_SB |393 |1.023 |2.201 |30% reduction |0.716 |807.883 |
## |CBS_MOTOR_SCORE |393 |1.913 |4.464 |30% reduction |1.339 |949.223 |
## |CBS_TOTAL_SCORE |393 |4.135 |9.895 |30% reduction |2.894 |998.776 |
## |PSPRS_TOTAL |324 |2.148 |6.172 |30% reduction |1.504 |1439.698 |
## |UPDRS_SCORE |341 |2.123 |6.484 |30% reduction |1.486 |1626.545 |
## |CBS_NONMOTOR_SCORE |393 |0.779 |2.447 |30% reduction |0.545 |1723.064 |
## |CBS_LCB_SCORE |393 |1.443 |5.243 |30% reduction |1.01 |2303.692 |8 AUC analyses
I completed these analyses with several subgroups including: controls, CBS, [CBS, PSP, nfvPPS, or ALS], etc. 8.1 bvFTD vs MCBI
## $`CBS_LCB_SCORE: bvFTD vs MCBI`
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## $`CBS_UNDERSTAND: bvFTD vs MCBI`
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## $`CBS_CARING: bvFTD vs MCBI`
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## $`CBS_THINKING: bvFTD vs MCBI`
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## $`CBS_FINANCE: bvFTD vs MCBI`
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## $`CBS_MULTITASK: bvFTD vs MCBI`
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## $`CBS_ACTINGAPP: bvFTD vs MCBI`
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## $`CBS_DIETPREF: bvFTD vs MCBI`
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## $`CBS_TOTAL_SCORE: bvFTD vs MCBI`
8.2 bvFTD or svPPA vs CBS or PSP
## $`CBS_MOTOR_SCORE: CBS_PSP vs bvFTD_svPPA`
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## $`CBS_INOUT: CBS_PSP vs bvFTD_svPPA`
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## $`CBS_WALKING: CBS_PSP vs bvFTD_svPPA`
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## $`CBS_EATING: CBS_PSP vs bvFTD_svPPA`
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## $`CBS_DRESSING: CBS_PSP vs bvFTD_svPPA`
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## $`CBS_HANDWRITING: CBS_PSP vs bvFTD_svPPA`
8.3 CBS, PSP, bvFTD, svPPA. vs nfvPPA
## $`CBS_SPEAKING: CBS_PSP_bvFTD_svPPA vs nfvPPA`
8.4 svPPA vs CBS, PSP
## $`CBS_MOTOR_SCORE: CBS_PSP vs svPPA`
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## $`CBS_INOUT: CBS_PSP vs svPPA`
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## $`CBS_WALKING: CBS_PSP vs svPPA`
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## $`CBS_EATING: CBS_PSP vs svPPA`
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## $`CBS_DRESSING: CBS_PSP vs svPPA`
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## $`CBS_TURNINGBED: CBS_PSP vs svPPA`
9 Longitudinal change by DX
These are the plots we spoke about when we met a few days ago. We have the average scores at baseline and at visit 2 for each diagnostic group. There are 2 versions of the plots. The “raw” is raw scores at time point 1 and 2. The annualized divides both baseline and followup scores by the retest interval. I did this because the retest interval is a little different across diagnoses.
9.1 Plots
## $CBS_TOTAL_SCORE
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## $CBS_MOTOR_SCORE
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## $CBS_NONMOTOR_SCORE
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## $CBS_LCB_SCORE
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## $FTLDCDR_SB
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## $PSPRS_TOTAL
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## $UPDRS_SCORE
9.2 Tables
## ### CBS_TOTAL_SCORE
##
##
## |dx_reduced | cbs_visit| avg| avg_time| n| annualized|dx_n |
## |:----------|---------:|---------:|--------:|---:|----------:|:-------------|
## |CBS | 1| 29.723404| 0.0000| 47| 34.164489|CBS (n=47) |
## |CBS | 2| 39.212766| 317.5532| 47| 45.071692|CBS (n=47) |
## |CU | 1| 2.153846| 0.0000| 169| 1.553010|CU (n=169) |
## |CU | 2| 1.786982| 506.2130| 169| 1.288486|CU (n=169) |
## |MCBI | 1| 7.421053| 0.0000| 19| 5.809346|MCBI (n=19) |
## |MCBI | 2| 9.736842| 466.2632| 19| 7.622192|MCBI (n=19) |
## |Other | 1| 8.214286| 0.0000| 14| 7.109587|Other (n=14) |
## |Other | 2| 6.642857| 421.7143| 14| 5.749492|Other (n=14) |
## |PSP | 1| 36.916667| 0.0000| 48| 47.518918|PSP (n=48) |
## |PSP | 2| 46.729167| 283.5625| 48| 60.149511|PSP (n=48) |
## |bvFTD | 1| 28.666667| 0.0000| 129| 24.854896|bvFTD (n=129) |
## |bvFTD | 2| 38.643411| 420.9767| 129| 33.505046|bvFTD (n=129) |
## |nfvPPA | 1| 17.484848| 0.0000| 33| 18.071478|nfvPPA (n=33) |
## |nfvPPA | 2| 23.848485| 353.1515| 33| 24.648619|nfvPPA (n=33) |
## |svPPA | 1| 20.804878| 0.0000| 41| 19.935011|svPPA (n=41) |
## |svPPA | 2| 27.658537| 380.9268| 41| 26.502113|svPPA (n=41) |
## ### CBS_MOTOR_SCORE
##
##
## |dx_reduced | cbs_visit| avg| avg_time| n| annualized|dx_n |
## |:----------|---------:|----------:|--------:|---:|----------:|:-------------|
## |CBS | 1| 14.2340426| 0.0000| 47| 16.3608040|CBS (n=47) |
## |CBS | 2| 19.1914894| 317.5532| 47| 22.0589615|CBS (n=47) |
## |CU | 1| 0.2011834| 0.0000| 169| 0.1450614|CU (n=169) |
## |CU | 2| 0.1420118| 506.2130| 169| 0.1023963|CU (n=169) |
## |MCBI | 1| 0.6842105| 0.0000| 19| 0.5356135|MCBI (n=19) |
## |MCBI | 2| 1.1052632| 466.2632| 19| 0.8652218|MCBI (n=19) |
## |Other | 1| 0.2142857| 0.0000| 14| 0.1854675|Other (n=14) |
## |Other | 2| 1.4285714| 421.7143| 14| 1.2364499|Other (n=14) |
## |PSP | 1| 17.9791667| 0.0000| 48| 23.1426787|PSP (n=48) |
## |PSP | 2| 23.6041667| 283.5625| 48| 30.3831460|PSP (n=48) |
## |bvFTD | 1| 5.7674419| 0.0000| 129| 5.0005524|bvFTD (n=129) |
## |bvFTD | 2| 9.8372093| 420.9767| 129| 8.5291680|bvFTD (n=129) |
## |nfvPPA | 1| 7.6969697| 0.0000| 33| 7.9552085|nfvPPA (n=33) |
## |nfvPPA | 2| 10.9393939| 353.1515| 33| 11.3064184|nfvPPA (n=33) |
## |svPPA | 1| 3.5121951| 0.0000| 41| 3.3653477|svPPA (n=41) |
## |svPPA | 2| 5.4634146| 380.9268| 41| 5.2349853|svPPA (n=41) |
## ### CBS_NONMOTOR_SCORE
##
##
## |dx_reduced | cbs_visit| avg| avg_time| n| annualized|dx_n |
## |:----------|---------:|---------:|--------:|---:|----------:|:-------------|
## |CBS | 1| 4.1276596| 0.0000| 47| 4.7443886|CBS (n=47) |
## |CBS | 2| 5.8723404| 317.5532| 47| 6.7497487|CBS (n=47) |
## |CU | 1| 0.8165680| 0.0000| 169| 0.5887785|CU (n=169) |
## |CU | 2| 0.7573964| 506.2130| 169| 0.5461134|CU (n=169) |
## |MCBI | 1| 1.8947368| 0.0000| 19| 1.4832374|MCBI (n=19) |
## |MCBI | 2| 2.5263158| 466.2632| 19| 1.9776498|MCBI (n=19) |
## |Other | 1| 2.7142857| 0.0000| 14| 2.3492547|Other (n=14) |
## |Other | 2| 1.6428571| 421.7143| 14| 1.4219173|Other (n=14) |
## |PSP | 1| 7.2500000| 0.0000| 48| 9.3321578|PSP (n=48) |
## |PSP | 2| 9.0208333| 283.5625| 48| 11.6115642|PSP (n=48) |
## |bvFTD | 1| 4.8449612| 0.0000| 129| 4.2007329|bvFTD (n=129) |
## |bvFTD | 2| 6.8139535| 420.9767| 129| 5.9079107|bvFTD (n=129) |
## |nfvPPA | 1| 3.2121212| 0.0000| 33| 3.3198902|nfvPPA (n=33) |
## |nfvPPA | 2| 3.7878788| 353.1515| 33| 3.9149648|nfvPPA (n=33) |
## |svPPA | 1| 3.2926829| 0.0000| 41| 3.1550134|svPPA (n=41) |
## |svPPA | 2| 4.0000000| 380.9268| 41| 3.8327571|svPPA (n=41) |
## ### CBS_LCB_SCORE
##
##
## |dx_reduced | cbs_visit| avg| avg_time| n| annualized|dx_n |
## |:----------|---------:|---------:|--------:|---:|----------:|:-------------|
## |CBS | 1| 11.361702| 0.0000| 47| 13.0592965|CBS (n=47) |
## |CBS | 2| 14.148936| 317.5532| 47| 16.2629816|CBS (n=47) |
## |CU | 1| 1.136095| 0.0000| 169| 0.8191701|CU (n=169) |
## |CU | 2| 0.887574| 506.2130| 169| 0.6399766|CU (n=169) |
## |MCBI | 1| 4.842105| 0.0000| 19| 3.7904955|MCBI (n=19) |
## |MCBI | 2| 6.105263| 466.2632| 19| 4.7793205|MCBI (n=19) |
## |Other | 1| 5.285714| 0.0000| 14| 4.5748645|Other (n=14) |
## |Other | 2| 3.571429| 421.7143| 14| 3.0911247|Other (n=14) |
## |PSP | 1| 11.687500| 0.0000| 48| 15.0440820|PSP (n=48) |
## |PSP | 2| 14.104167| 283.5625| 48| 18.1548013|PSP (n=48) |
## |bvFTD | 1| 18.054264| 0.0000| 129| 15.6536110|bvFTD (n=129) |
## |bvFTD | 2| 21.992248| 420.9767| 129| 19.0679667|bvFTD (n=129) |
## |nfvPPA | 1| 6.575758| 0.0000| 33| 6.7963789|nfvPPA (n=33) |
## |nfvPPA | 2| 9.121212| 353.1515| 33| 9.4272353|nfvPPA (n=33) |
## |svPPA | 1| 14.000000| 0.0000| 41| 13.4146498|svPPA (n=41) |
## |svPPA | 2| 18.195122| 380.9268| 41| 17.4343706|svPPA (n=41) |
## ### FTLDCDR_SB
##
##
## |dx_reduced | cbs_visit| avg| avg_time| n| annualized|dx_n |
## |:----------|---------:|---------:|--------:|---:|----------:|:-------------|
## |CBS | 1| 4.9042553| 0.0000| 47| 5.6370184|CBS (n=47) |
## |CBS | 2| 6.8191489| 317.5532| 47| 7.8380235|CBS (n=47) |
## |CU | 1| 0.0000000| 0.0000| 169| 0.0000000|CU (n=169) |
## |CU | 2| 0.0000000| 506.2130| 169| 0.0000000|CU (n=169) |
## |MCBI | 1| 1.6578947| 0.0000| 19| 1.2978327|MCBI (n=19) |
## |MCBI | 2| 1.9473684| 466.2632| 19| 1.5244384|MCBI (n=19) |
## |Other | 1| 0.8571429| 0.0000| 14| 0.7418699|Other (n=14) |
## |Other | 2| 1.0357143| 421.7143| 14| 0.8964262|Other (n=14) |
## |PSP | 1| 5.0104167| 0.0000| 48| 6.4493792|PSP (n=48) |
## |PSP | 2| 6.2291667| 283.5625| 48| 8.0181471|PSP (n=48) |
## |bvFTD | 1| 7.4302326| 0.0000| 129| 6.4422440|bvFTD (n=129) |
## |bvFTD | 2| 9.7945736| 420.9767| 129| 8.4922016|bvFTD (n=129) |
## |nfvPPA | 1| 3.0909091| 0.0000| 33| 3.1946113|nfvPPA (n=33) |
## |nfvPPA | 2| 4.6363636| 353.1515| 33| 4.7919169|nfvPPA (n=33) |
## |svPPA | 1| 5.9512195| 0.0000| 41| 5.7023947|svPPA (n=41) |
## |svPPA | 2| 8.3292683| 380.9268| 41| 7.9810155|svPPA (n=41) |
## ### PSPRS_TOTAL
##
##
## |dx_reduced | cbs_visit| avg| avg_time| n| annualized|dx_n |
## |:----------|---------:|----------:|--------:|---:|----------:|:-------------|
## |CBS | 1| 20.6153846| 0.0000| 39| 24.6625767|CBS (n=39) |
## |CBS | 2| 28.3589744| 305.1026| 39| 33.9263804|CBS (n=39) |
## |CU | 1| 0.3092105| 0.0000| 152| 0.2317335|CU (n=152) |
## |CU | 2| 0.3092105| 487.0329| 152| 0.2317335|CU (n=152) |
## |MCBI | 1| 1.0714286| 0.0000| 14| 0.7904996|MCBI (n=14) |
## |MCBI | 2| 2.0000000| 494.7143| 14| 1.4755992|MCBI (n=14) |
## |Other | 1| 1.5384615| 0.0000| 13| 1.3227034|Other (n=13) |
## |Other | 2| 1.6153846| 424.5385| 13| 1.3888386|Other (n=13) |
## |PSP | 1| 31.5142857| 0.0000| 35| 43.1459651|PSP (n=35) |
## |PSP | 2| 38.1142857| 266.6000| 35| 52.1819741|PSP (n=35) |
## |bvFTD | 1| 6.0462963| 0.0000| 108| 5.2940850|bvFTD (n=108) |
## |bvFTD | 2| 7.7592593| 416.8611| 108| 6.7939406|bvFTD (n=108) |
## |nfvPPA | 1| 6.6666667| 0.0000| 27| 6.9391635|nfvPPA (n=27) |
## |nfvPPA | 2| 10.6296296| 350.6667| 27| 11.0641107|nfvPPA (n=27) |
## |svPPA | 1| 2.7105263| 0.0000| 38| 2.6049751|svPPA (n=38) |
## |svPPA | 2| 4.1052632| 379.7895| 38| 3.9453991|svPPA (n=38) |
## ### UPDRS_SCORE
##
##
## |dx_reduced | cbs_visit| avg| avg_time| n| annualized|dx_n |
## |:----------|---------:|----------:|--------:|---:|----------:|:-------------|
## |CBS | 1| 20.4054054| 0.0000| 37| 24.9637648|CBS (n=37) |
## |CBS | 2| 28.8108108| 298.3514| 37| 35.2468521|CBS (n=37) |
## |CU | 1| 0.0833333| 0.0000| 156| 0.0617372|CU (n=156) |
## |CU | 2| 0.0897436| 492.6795| 156| 0.0664862|CU (n=156) |
## |MCBI | 1| 1.2500000| 0.0000| 16| 0.9511401|MCBI (n=16) |
## |MCBI | 2| 1.7500000| 479.6875| 16| 1.3315961|MCBI (n=16) |
## |Other | 1| 0.3846154| 0.0000| 13| 0.3306758|Other (n=13) |
## |Other | 2| 0.3076923| 424.5385| 13| 0.2645407|Other (n=13) |
## |PSP | 1| 22.9024390| 0.0000| 41| 29.8940253|PSP (n=41) |
## |PSP | 2| 29.3170732| 279.6341| 41| 38.2668993|PSP (n=41) |
## |bvFTD | 1| 2.8303571| 0.0000| 112| 2.4645352|bvFTD (n=112) |
## |bvFTD | 2| 3.6160714| 419.1786| 112| 3.1486964|bvFTD (n=112) |
## |nfvPPA | 1| 4.3928571| 0.0000| 28| 4.4984970|nfvPPA (n=28) |
## |nfvPPA | 2| 9.7857143| 356.4286| 28| 10.0210421|nfvPPA (n=28) |
## |svPPA | 1| 0.3846154| 0.0000| 39| 0.3697076|svPPA (n=39) |
## |svPPA | 2| 0.8717949| 379.7179| 39| 0.8380039|svPPA (n=39) |