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Manual Therapy Utrecht for Neck Pain

Groeneweg, R.

2017

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citation for published version (APA)Groeneweg, R. (2017). Manual Therapy Utrecht for Neck Pain: (Cost-)effectiveness, reporting guideline formanual interventions, prediction in treatment success.

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Download date: 28. Feb. 2021

173

Chapter 7

Categorizing patients with neck pain has implications for

outcome success.

Ruud GroenewegRaymond WJG Ostelo

Michiel R de BoerArianne P Verhagen

Jan JM PoolFrieke Vonk

Rob AB OostendorpMaurits W van Tulder

Submitted

177176

ABSTRACT

The STarT Back Tool (SBT) was developed to allow identification of high, medium and low risk profiles for poor prognosis of low back pain patients in primary care. The purpose of the present study is to explore the potential of a similar short screening tool designed to identify risk profiles in patients with neck pain.

METHODSQuestionnaire items from three randomized clinical trials (RCTs) on neck pain conducted in the Netherlands were selected based on comparability to constructs in the SBT. The risk profile of each patient was classified as high, medium or low. Generalized estimating equation (GEE) analyses were performed on recovery for each risk profile at 6-9, 26 and 52 weeks.

RESULTSA total of 466 patients were included; 70.7% showed low, 23.3% medium and 6.0% high-risk profiles. The three risk profiles differed significantly at baseline on pain, functioning and physical and mental health. An overall statistically significant relation was found between the risk profiles and recovery (Wald Chi square, 6.72; p=.035); Odds ratio’s were statistically significant at 26 weeks (low versus medium-risk: .54 (95% CI: .32 to .90)) and at 52 weeks (low versus high-risk: .41 (95% CI: .17 to .99)), but not at 6-9 weeks.

CONCLUSIONSLow, medium, and high-risk profiles for a poor neck pain prognosis can be distinguished by a short set of items. Overall, our study illustrates that the higher the risk profile, the lower the odds for recovery with clinically relevant differences. Future research should first focus on establishing and improving the psychometric characteristics of the tool, before evaluation of its predictive value in a larger cohort.

Key words: neck pain, risk, prognosis

7

INTRODUCTIONNeck pain ranks fourth worldwide in terms of ‘Years Lived with Disability’1, is common and has a significant economic impact due to high work absenteeism2,3. In a cohort study, 48% of people with neck pain still had persistent symptoms after 1 year4. Categorizing patients with neck pain into subgroups based on their functional prognosis has been and remains an important issue5. Patients with neck pain form a heterogeneous group which can be divided into clinical subgroups for guided decision-making regarding specific treatments. Several attempts have been made previously to classify patients with neck pain6,7 or to develop clinical decision rules8-10.

Both physical and psychosocial variables have been shown to be prognostic for poor outcome or work absence in patients with neck pain. Physical variables include pain5,9,11-13, disability13, and accompanying low back pain9, whereas psychosocial variables involve catastrophizing13,14, fear of movement, anxiety and depression13, and poor general15 or mental health5. A short screening tool for neck pain that includes questions designed to identify and combine these variables might have added value for both clinical research and clinical practice, as it would allow prediction of a poor prognosis and aid in initial decision-making aimed at delivering targeted treatments.

The STarT Back Tool (SBT) was developed to facilitate identification of prognostic subgroups of low back pain patient16. It is a nine-item questionnaire that is used for determining the prognosis for poor treatment outcomes by screening patients with nonspecific low back pain in primary care. The SBT takes about two minutes to complete, and contains eight yes/no questions (Q1-Q8) and one question (Q9) that uses a five-point Likert scale. It consists of questions and queries about radiating leg pain and pain elsewhere (comorbidity), disability, fear, anxiety, pessimistic patient expectations, mood, and bothersomeness. The SBT classifies patients into one of three possible risk profiles for stratified primary care management: low-risk, medium-risk (physical indicators), and high-risk (physical and psychosocial indicators). The SBT is found to be a reliable and valid instrument for classifying low back pain patien16. To date it has been translated and validated for Iranian17, French18, Danish19 and German20,21, and translated into Spanish22.

7

179178

Based on the SBT risk profiles (risk stratification), appropriate targeted treatments can be provided to patients. A large randomized controlled trial (RCT) showed that stratified treatment based on an SBT risk profile was statistically significantly more effective in reducing levels of disability as compared with non-stratified general best practice management approaches23. The challenge now is to assess if the same holds true for patients with neck pain. Therefore, the aims of this study were: 1) to explore the potential of a screening tool in terms of its ability to identify risk profiles for patients with neck pain, and 2) to explore the predictive validity of these risk profiles on recovery in patients with nonspecific neck pain in primary care.

METHODS

DesignThis concerns a secondary analysis of data of three similar RCTs performed in primary physical therapy care in the Netherlands24-26.

Data CollectionData from the three RCTs were combined, all of which evaluated the effectiveness of primary care interventions for patients with nonspecific neck pain24-26. The patients received different treatments as experimental intervention or as control, including physical/exercise therapy (n=162)24,26, manual therapy (n=165)25,26, or a behavioral-graded activity program (n=139)24,25.

Trial PopulationThe trials had similar eligibility criteria and consisted of a primary care population, aged 18 to 70 years, with nonspecific neck pain, defined as neck pain without a known pathologic basis. Participants with a specific disorder (e.g., herniated disc, neurologic disorder, infection, malignancy, surgery, or fractures) were excluded from the trials.

STarT Back Tool and constructing a neck pain screening toolThe SBT was developed to allow physicians or therapists to screen patients for prognostic indicators of back pain relevant to initial decision-making in primary

7

care, and to categorize patients to specific risk profiles (low, medium and high risk). It produces two scores that can differentiate the low-risk from the medium and high-risk profiles: an overall score and a distress subscale score. The range of possible scores varies from 0 to 9 and is obtained by summarizing all positive items. Question 9, scored on a 5-point Likert scale, is also dichotomized, with ‘very much’ and ‘extremely’ categorized as ‘yes’ and the other answers categorized as ‘no’. Patients with a total score of 0-3 are classified as low risk and those who score 4 to 9 are categorized as either medium or high risk. The distress subscale score, which includes the questions 5 to 9 (fear, anxiety, catastrophizing, depression, and bothersomeness), is used to further classify the medium and high-risk subgroups. Scores on this subscale range from 0 to 5, with scores of 4 or 5 indicating high risk.

Starting from the questionnaires used in the three RCTs 24-26, we selected items based on face validity that were in line with the constructs of the original SBT (see Table 1). Table 1 presents the questionnaires and how each variable was dichotomized. The questionnaires used included: patient intake, Neck Disability Index (NDI), Tampa Scale for Kinesiophobia (TSK), Fear Avoidance Beliefs Questionnaire (FABQ), Quality of Life (EuroQol), and the SF-36. Answers on each selected item were dichotomized in agree/disagree in accordance with the SBT. Below we describe in more detail how each variable was selected and describe how the original variables in the trials were dichotomized. Questions 1 and 2 were on comorbidity and were selected from items included in history taking at baseline. Questions 3 and 4 were about limitations of functioning and were extracted from the Neck Disability Index (NDI)24-26: NDI item 2 (‘personal care’ – washing, dressing) and item 3 (‘lifting’). The 6-point Likert scales of the NDI were dichotomized into ‘disagree’ (0-1 points) and ‘agree’ (2-5 points). Question 5 was extracted from the Tampa Scale for Kinesiophobia (TSK, item 14) out of Vonk et al., and Pool et al.24,25. The 4-point scale of the TSK was dichotomized into disagree (‘strongly disagree’ and ‘disagree’) and agree (‘agree’ and ‘strongly agree’). Alternatively, item four of the Fear Avoidance Beliefs Questionnaire (FABQ) was used out of Groeneweg et al.26.Question 6 was derived from item 5 of the EuroQol24-26: ‘I am not anxious or depressed’ was labeled as ‘disagree’; ‘I am moderately anxious or depressed’ or ‘I

7

181180

Cons

truct

Que

stions S

BTQue

stions N

eck To

olDich

otom

ized

Stud

yQ1

Comorbidity

My ba

ck p

ain ha

s sp

read

dow

n m

y

leg(

s) at so

me

time

in the

last

2 we

eks

My ne

ck p

ain ha

s sp

read d

own

my arm(s) a

t som

e tim

e in

the

last

2 we

eks (In

take

)

1,2

Q2

Comorbidity

I ha

ve ha

d pa

in in

the

shou

lder

or n

eck at

some

time

in the

last

2 we

eks

I ha

ve ha

d pa

in in

the

low

back a

t som

e tim

e in

the last

2 we

eks (In

take

)

1,2,3

Q3

Disa

bility

I hav

e on

ly w

alke

d sh

ort

dist

ance

s

beca

use of

my ba

ck p

ain (RMDQ

)Lifting (ND

I, Q

3)0-1 pts:

disa

gree

; 2-5 p

ts: a

gree

1,2,3

Q4

Disa

bility

In the last

2 we

eks,

I hav

e dr

esse

d

mor

e sl

owly t

han

usua

l be

caus

e ofba

ck p

ain (RMDQ

)

Person

al ca

re (was

hing

, dres-

sing

) (ND

I, Q

2)0-1 pts:

disa

gree

; 2-5 p

ts: a

gree

1,2,3

Q5

Fear

It’s no

t rea

lly safe for a p

erso

n with

acon

ditio

n like mine to b

e ph

ysi-

callyac

tive (TSK

)

It’s no

t rea

lly s

afe for a

perso

n with

a co

ndition like

mine

to

be p

hysic

ally ac

tive (TSK

, Q 14)

‘strong

ly disa

gree

’ and ‘disa

gree

’: disa

gree

‘agree

’ an

d ‘st

rong

ly ag

ree’: a

gree

1,2

I sho

uld no

t do p

hysica

l acti-

vities wh

ich

(might) mak

e my

pain

worse(FA

BQ, Q

4)

0-4 pts:

disa

gree

; 5-6 p

ts: a

gree

3

Q6

Anxie

tyW

orry

ing

thou

ghts

ha

ve

been

going throug

h my mind a lot o

f the

time(HA

DS)

Anxie

ty/D

epression

(EuroQ

ol,

Q 5)

‘I am

not a

nxious o

r de

pres

sed’:

disa

gree ‘I

am m

oderately an

xious

or d

epressed

’ or ‘I am

extremely

anxio

us o

r dep

ressed

’: ag

ree

1,2,3

7

Tabl

e 1

Que

stio

ns s

elec

ted

to d

iffe

rent

iate

pro

gnos

tic

subg

roup

s in

nec

k pa

in p

atie

nts

Q7

Pessim

istic

patie

ntex

pectations

I fee

l that

my

back

pai

n is

ter

ri-

ble an

d it’s n

ever

goi

ng t

o ge

t an

y

bett

er (P

CS)

My ac

cide

nt ha

s pu

t my bo

dy

at ris

k for the

rest

of my life

(TSK

, Q 6

)

‘strong

ly disa

gree

’ and ‘disa

gree

’: disa

gree

‘agree

’ and ‘s

trong

ly ag

ree’: a

gree

1,2

My wo

rk mak

es o

r wou

ld mak

e my pa

inwo

rse (FAB

Q, Q

10)

0-4 pts:

disa

gree

; 5-6 p

ts: a

gree

3

Q8

Moo

dIn

gene

ral I

have n

ot e

njoy

ed a

ll the things I

used to en

joy (HAD

S)Ha

ve

you

felt

down

hearted

and blue

? (SF-36

, Q 9

f)‘non

e of

the tim

e’, ‘a little o

f the

time’: d

isag

ree ‘so

me of

the tim

e’,

‘a go

od b

it of

the tim

e’, ‘mos

t of

the tim

e’, ‘all o

f the tim

e’: a

gree

1,2,3

Q9

Botherso

men

ess

Ove

rall,

how

both

erso

me ha

s yo

urba

ck pain be

en in

the la

st 2

wee

ks?

Durin

g the pa

st 4 we

eks,

how

muc

h did

pain

interfe

re with

your no

rmal

work

(includ

ing

both

work

outside the ho

me

and ho

usew

ork)? (SF-36

, Q 8

)

score

corre

spon

ding SB

T qu

es-

tion

1,2,3

Abb

revi

atio

ns:

Q,

Que

stio

n; S

BT,

STar

T Ba

ck T

ool;

RM

DQ

, Ro

land

and

Mor

ris

Dis

abil

ity

Que

stio

nnai

re;

TSK,

Tam

pa S

cale

of

Kine

soph

obia

; H

AD

S.

Hos

pita

l Anx

iety

and

Dep

ress

ion

Scal

e; P

CS,

Pain

Cat

astr

ophi

zing

Sca

le;

ND

I, N

eck

Dis

abil

ity

Scal

e; F

ABQ

, Fe

ar A

void

ance

Bel

ief

Que

stio

nnai

re;

SF-

36,

Shor

t Fo

rm-3

6; p

ts,

poin

ts;

stud

y 1,

Von

k; s

tudy

2,

Pool

; st

udy

3,G

roen

eweg

.

7

183182

am extremely anxious or depressed’ as agree. Question 7 in the SBT originated from the TSK and was dichotomized in the same way as item 524,25. Alternatively, this item was derived from the FABQ (item 10)26.For question 8 the following item was selected from the SF-36 (item 9f) ‘Have you felt downhearted and blue?’ The response to this item was dichotomized into: ‘disagree’ (none of the time, a little of the time) and ‘agree’ (some of the time, a good bit of the time, most of the time, all of the time)24-26.Question 9 was derived from the SF-36 (item eight) and has the same Likert score as the corresponding SBT question24-26.Low, medium and high-risk profiles were similarly classified based on the screening tool scores as in the original SBT for low back pain.In addition we conducted a sensitivity analysis in which different cutoff scores were used to dichotomize items one to four in the original questionnaires, and we also used an alternative item for the NDI (item 10 ‘recreation’ instead of item 2). More specifically, for questions 1 and 2, besides pain other clinical signs such as pins and needles and numbness in the extremities were included for ‘agree’, and for Q3 and Q4 the 6-point Likert scales of the NDI were dichotomized into ‘disagree’ (0 points) and ‘agree’ (1-5 points). Outcome measurementsIn all three RCTs the outcomes were measured at 3 time points: 6 to 9 weeks (short-term),26 (intermediate-term) and 52 weeks (long-term). Recovery was measured using global perceived effect (GPE)24-26 measured on a 7-point ordinal Likert scale (1, recovered; 2, much improved; 3, a little improved; 4, not changed; 5, a little worse; 6, much worse; and 7 worst ever). The outcome was dichotomized into “recovered” (a score of 1 or 2 on the GPE) and “persistent complaints” (a score of 3 to 7 on the GPE). GPE has a high face validity27 and an excellent test-retest reliability28.

Statistical analysisThe raw data of the three studies were merged and subsequently cleaned. Descriptive analyses of baseline characteristics were performed for demographics (age, gender) and clinical signs (pain, disability, quality of life). Low, medium and high-risk profiles were compared by analysis of variance (ANOVA) for the baseline

7

Variable Study 1* Study 2** Study 3*** Total MT PT BGANumber of patients (n; %)

139 (29.8) 146 (31.3) 181 (38.8) 466

Manual Therapy(n; %)

75 (45.5) 90 (54.5) 165 165 (35.4)

Physical Therapy (n; %)

71 (43.8) 91 (56.2) 162 162 (34.8)

BGA program (n; %)

68 (48.9) 71 (51.1) 139 139 (29.8)

Age (in years,mean; SD)

45.7 (12.4) 45.1 (11.5) 49.0 (12.5) 46.8 (12.3) 47.6 (11.9)

47.4 (12.7)

45.1 (12.1)

Gender, female (n; %)

86 (61.9) 89 (61.0) 112 (61.9) 287 (61.6) 103 (62.4)

99 (61.1) 85 (61.2)

Complain intensityT0 (NRS 0-10)(mean; SD)

6.8 (1.5) 6.9 (1.4) 6.9 (1.3) 6.9 (1.4) 6.9 (1.4) 6.9 (1.5) 6.9 (1.4)

NDI, T0 (0-50)(mean; SD)

15.2 (6.2) 14.0 (6.8) 12.1 (6.1) 13.6 (6.5) 12.9 (7.1) 13.2 (5.9)

14.9 (6.3)

NRS-P, T0 (0-10)(mean; SD)

6.9 (1.8) 5.3 (2.2) 5.7 (1.9) 5.9 (2.1) 5.4 (2.1) 6.3 (1.8) 6.1 (2.2)

PCS, T0 (0-100)(mean; SD)

39.6 (5.7) 43.7 (7.7) 44.6 (7.5) 42.9 (7.4) 44.7 (7.6) 42.4 (7.0)

41.2 (7.0)

MCS, T0 (0-100)(mean; SD)

43.4 (6.2) 47.2 (11.8) 46.8 (11.3) 46.0 (10.4)

46.9 (12.4)

45.7 (8.8)

45.1 (9.5)

Low risk (n; %) 71 (62.8) 88 (67.2) 135 (78.5) 294 (70.7) 110 (66.7) 112 (69.1)

71 (51.8)

Medium risk (n %)

35 (31.0) 38 (29.0) 24 (14.0) 97 (23.3) 32 (19.4) 29 (17.9) 36 (25.9)

High risk (n %) 7 (6.2) 5 (3.8) 13 (7.6) 25 (7.6) 12 (7.3) 7 (4.3) 6 (4.3)Abbreviations: * Vonk et al (1), ** Pool et al (2), *** Groeneweg et al. (3); MT, Manual Therapy; PT,

Physical Therapy; BGA, Behavioral Graded Activity; n, number; SD, Standard Deviation;; NDI, Neck

Disability Index; NRS-P. Numeric Rating Scale for Pain; PCS, Physical Component Scale of Short

Form-36; MCS, Mental Component Scale of Short Form-36; T0, baseline measurement; SNT, ‘STarT

Neck Tool’.

Table 2 Baseline characteristics of the three included RCTs and treatment groups

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185184

scores of pain, functioning, physical and mental health, with Bonferroni post-hoc tests.Due to the longitudinal nature of the data, generalized estimating equations (GEE) were performed to evaluate the effect on recovery for each risk profile, entering interventions as a possible confounder as well as age and sex. Odds Ratios (OR) with 95% confidence intervals (CI) are reported. Sensitivity analysis was performed with different cutoff scores for the Likert scales and by using other questions from the trials. Missing data were not imputed. Statistical significance was set at α≤ .05 and the IBM Statistical Package for the Social Sciences (SPSS), version 23 was used.

RESULTS

In total 466 patients were included in the RCTs, with an overall mean age of 46.8 years, 61.6% of whom were female (SD=12.3). The trial populations were similar at baseline and did not meaningfully differ on baseline scores for complaint intensity, NDI, NRS-P, and physical (PCS) and mental (MCS) component scores of the SF-36 (see Table 2). Data of 50 participants (out of the 466 included participants) were missing and these participants were excluded from the analysis.The overall prevalence of risk profiles was 70.7% (n=294) for low risk, 23.3% (n=97) for medium risk, and 6.0% (n=25) for the high-risk profile, with only minor differences between the three trials (see Table 2). The three risk profiles differed significantly at baseline on NDI, NRS-P, PCS and MCS, with the exception of medium and high-risk on PCS. Scores related to worse complaints at baseline corresponded to higher risk profiles.Table 3 and Figure 2 show the outcomes for recovery per risk profile. At short-term follow-up the percentage recovered patients for the low, medium and high-risk profiles were 51.6%, 46.7% and 36.0% respectively; at intermediate-term follow-up 62.8%, 48.1% and 45.0%; and at long-term follow-up 64.8%, 56.8% and 45.0%. An overall statistically significant relation was found between the risk profiles and recovery (Wald Chi square, 6.72; p=.035). The results in Table 4 indicate that the higher the risk profile, the lower the odds for recovery. For example, in the adjusted analysis at 52 weeks, the OR for medium compared with low risk was 0.69 (95%CI: 0.42 to 1.16) and the OR for high compared with low risk was 0.41 (95% CI: 0.17

7

Variable Low risk Mediumrisk

High risk OverallP value

p-value*Low/medium

p- value*Low/high

p- value*Medium/high

Age (in ears, mean; SD)

47.1 (12.1) 47.9 (12.1) 48.1 (11.9) .814

Gender, female (n; %)

177 (60.2) 65 (67.0) 15 (60.0) 482

Complain intensity (NRS-P, 0-10) (mean; SD)

6.7 (1.4) 7.1 (1.1) 7.9 (1.2) .000 .032 .000 .011

NDI, T0 (0-50) (mean; SD)

11.3 (5.2) 18.0 (5.6) 21.9 (7.5) .000 .000 .000 .004

NRS-P, T0 (0-10) (mean; SD)

5.6 (2.0) 6.4 (1.8) 7.6 (1.6) .000 .002 .000 .013

PCS, T0 (0-100) (mean; SD)

44.4 (7.1) 40.2 (6.9) 37.8 (7.0) .000 .000 .000 .050

MCS, T0 (0-100) (mean; SD)

48.9 (8.9) 40.3 (10.2) 35.1 (11.5) .000 .000 .000 .049

T1 recovered (n; %)

142 (51.6) 42 (46.7) 9 (36.0)

T2 recovered (n; %)

162 (62.8) 39 (48.1) 9 (45.0)

T3 recovered (n; %)

169 (64.8) 46 (56.8) 9 (45.0)

Abbreviations: n, number; SD, Standard Deviation; NDI, Neck Disability Index; NRS-P. Numeric

Rating Scale for Pain; PCS, Physical Component Scale of Short Form-36; MCS, Mental Component

Scale of Short Form-36; GPE, Global Perceived Effect; T0, baseline measurement; T1, 6-9 weeks

measurement; T2, 26 weeks measurement; T3, 52 weeks measurement, *with Bonferroni correction.

Table 3 Baseline characteristics and outcome (recovery) of the three risk groups

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Timing Comparison

Low Risk

OR 95% CI

T1 (6-9 weeks)Medium Risk .82 .50 to 1.34High Risk .66 .27 to 1.62

T2 (26 weeks)Medium Risk .54 .32 to .90High Risk .42 .17 to 1.05

T3 (52 weeks)Medium Risk .69 .42 to 1.16High Risk .41 .17 to .99

Abbreviations: OR, Odds Ratio; p-value; CI, Confidence Interval; GPE, Global Perceived Effect.

Adjusted for age, sex, and intervention.

Table 4 Results of Generalized Estimating Equations (GEE) analyses on recovery (GPE) for risk groups compared to low risk

to 0.99). For the separate time points, the odds for recovery between low versus medium risk at 26 weeks (54 (95% CI; .32 to .90) and between low versus high risk at 52 weeks (.41 (95% CI; .17 to .99) were statistically significantly different. Sensitivity analysis (with different cutoff scores for the SBT items and substituting items for functioning on the SBT) showed a different distribution of risk profiles (39.9% low, 52.4% medium and 7.7% high risk), but associations with recovery were similar.

DISCUSSION

This study assessed the development and validity of a screening tool to identify risk profiles in patients with neck pain at baseline, with the aim of facilitating the identification of patient prognosis. Using data from three RCTs conducted in the Netherlands24-26 and selecting the possibly relevant questionnaires available from the 3 trials, we were able to cover all domains of the original SBT for low back pain (SBT). These profiles are similar in construct to the profiles in the Dutch guideline for the treatment of neck pain. In this guideline profile A includes patients with a normal course, profile B patients with a deviant course without dominant

7

psychosocial obstructive factors, and profile C patients with a deviant course with dominant psychosocial obstructive factors 29.Our study suggests that risk profiles indicating a low, medium or high risk for poor prognosis for neck pain can be distinguished at baseline by a short set of items, similar to the SBT. Our overall results suggest that the higher the risk profile, the lower the odds for recovery. Based on the assumptions in the initial RCTs used in this study30-32, the observed differences in recovery of 20% can be considered as clinically relevant.Differences in the prevalence of risk profiles between the three trials might be explained by the differences in baseline scores of the individual trials, with a higher prevalence of the low-risk profile in the trial by Groeneweg et al.26 (79%) compared to the other trials (63-67%)24,25. The trial by Vonk et al.24 included chronic patients and Pool et al.25 included sub-acute patients, whereas Groeneweg et al.26 included sub-acute and chronic patients. It is notable that while Vonk et al.24 included only chronic patients, an equally small proportion of these patients were classified as having a high-risk profile. High risk for a poor outcome does not seem to be the same as having chronic complaints. In our sensitivity analyses we tested cutoff points whereby more questions were categorized as ‘agree’. This resulted in a lower proportion of low-risk and a higher proportion of medium-risk profiles, but the group with a high-risk profile remained small. As the sensitivity analyses produced similar results, we conclude that our results were not influenced by the choice of cutoff for individual answers to the questions used.Compared to the literature on low back pain, our study showed a relatively high prevalence of low risk and relatively low prevalence of high-risk patients based on the outcome of the screening tool (see Table 2). The relative distribution of the three risk profiles in low back pain studies varies, ranging between 33-42% for the low-risk profiles, 32-48 % for medium-risk profiles, and between 19-28 % for high-risk profiles33-39. Only one exception has been published: in a study in chiropractic clinics 59% of patients had a low-risk profile, while only 11% had a high-risk profile37. Our study seems to suggest that the distribution of risk profiles is somewhat different in neck pain, with 71% having a low-risk profile and only 6% with a high-risk profile. Lowering the cutoff values only slightly altered the distribution of risk (40% had a low-risk profile and 8% a high-risk profile). The high prevalence of low-risk profile in our study could partly be explained by a low baseline score

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on the NDI in all three RCTs, with an overall mean of 13.6 points (SD=6.5). This can be considered as representing no to mild disability40,41. Likewise, the low prevalence of high-risk profiles for neck pain in our study may also be explained by low baseline scores in the three RCTs24-26 on questionnaires with constructs related to the conceptual model of emotional reaction, such as fear, anxiety and worry. It is questionable if scores on these constructs in neck pain patients are comparable with scores in low back pain patients. Future research should focus on identifying the optimal cutoff values for these items when included in a screening tool for neck pain. A 6% prevalence for the high-risk profile is low, but high risk for poor prognosis has meaningful individual, clinical and socioeconomic consequences. In the protocol for stratified treatment in back pain patients16 based on the results of the SBT, all patients received reassurance regarding the benign nature of their pain and a clear explanation of pain relief, appropriate activity levels and the role of further investigations. This was supported by a 15 minute video. For patients in the low-risk profile, this was the only intervention. Patients in the medium-risk profile received six 30-minute sessions that applied a range of physical therapy techniques. Patients with a high-risk profile received a tailored treatment using cognitive behavioral strategies. In the three neck pain RCTs, patients were randomized to physical therapy/exercise therapy (n=162), manual therapy (n=165), or a behavioral-graded activity program (n=139) using a protocol that was not targeted to a risk profile. The treatments roughly approximate the intervention aimed at the medium- and high-risk profile in the SBT protocol. In accordance with the Dutch guideline, treatment for the high-risk group included discussion of the psychosocial aspects and exercise therapy based on the principles of behavioral graded activity29. Consequently, some over-treatment in low-risk patients and under-treatment in high-risk patients might have occurred in the neck pain RCTs underlying this study. This may have resulted in higher direct costs (over-treatment) and decreased effectiveness (under-treatment). This will be needed to be determined in future studies of stratified care for neck pain.The findings of this study should be interpreted in light of certain limitations. Although the questions in our study were more or less similar to the SBT questions,

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we could only use items available in the questionnaires included in the RCTs. We used face validity of each selected item. However, the results seem to be independent of choices of questions or cutoff scores, as no differences in outcome were observed when using different cutoff points or slightly different items from the available questionnaires.The original SBT was not designed simply as a prognostic tool, but also for treatment stratification followed by targeted treatments offered to groups with a low, medium and high-risk for a poor prognosis. In our study this treatment stratification was not performed, so our results do not convey direct information on effects of targeted therapy based on the risk profiles. Another limitation was the choice of only one outcome variable. The other outcome variables used in all three trials were pain and functioning. However, as these two constructs were items included in the screening tool to identify the risk profile, we refrained from using these as outcomes in our study. Also recovery has shown to capture patients’ perceptions on different domains important to their individual experiences42.A strength of the study was the use of GEE analysis, which meant that both the overall differences between the three risk profiles over time, as well as differences on separate measurement moments could be analyzed, while accounting for correlated observations over time.

A relatively large group of patients in clinical practice display neck pain symptoms, even after intervention. In our study about 45 % had no or only slight improvement after 52 weeks. It is important, both from an individual as well as social perspective, to reduce this number, especially as patients with chronic complaints consume a significant portion of the total cost of care.This study is a first step in a research effort to identify subgroups of patients with non-specific neck pain and to eventually provide targeted treatments, assuming that these will produce improved recovery and lower costs. This is in the interest of not only the patients themselves, but will also benefit policy makers and insurance companies.

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CONCLUSIONS

Our study indicates that low, medium, and high-risk profiles for a poor neck pain prognosis can be distinguished by a short set of items, similar to the SBT for low back pain. We found statistically significant differences between the risk profiles at baseline. Overall, our study illustrates that the higher the risk profile, the lower the odds for recovery. Future research should first focus on establishing and improving the psychometric characteristics of the tool, before evaluation of its predictive value in a larger cohort.

Competing interestsThere are no conflicts of interests, there was no funding for this project.

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Figure 1 Percentage of patients recovered on global perceived effect (GPE) in low, medium and high-

risk profile groups in T1 (6-9 weeks), T2 (26 weeks) and T3 (52 weeks)

06-9 wk

36

45

48

52

63 65

47

57

45

High risk

Medium risk

Low risk

% re

cove

red

GPE

26 wk 52 wk

20

40

80

100

60

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REFERENCES

1 Vos T, et al. Years lived with disability (YLDs) for 1160 sequelae of289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. The Lancet. 2012 15;380:2163–96.

2 Fejer R, Kyvik KO, Hartvigsen J. The prevalence of neck pain in the world population: a systematic critical review of the literature. Eur Spine J. 2006 6;15(6):834–48.

3 Borghouts JA, Koes BW, Vondeling H, Bouter LM. Cost-of-illness of neck pain in The Netherlands in 1996. Pain. 1999;80(3):629–36.

4 Hill J, Lewis M, Papageorgiou AC, Dziedzic K, Croft P. Predicting persistent neck pain: a 1-year follow-up of a population cohort. Spine. 2004;29(15):1648–54.

5 Bergström C, Hagberg J, Bodin L, Jensen I, Bergström G. Using a psychosocial subgroup assignment topredict sickness absence in a working populationwith neck and back pain. BMC Musculoskelet Disord. 2011;12(1):81.

6 Childs JD, Fritz JM, Piva SR, Whitman JM. Proposal of a classification system for patients with neck pain. J Orthop Sports Phys Ther. 2004;34(11):686–96.

7 Fritz JM, Brennan GP. Preliminary examination of a proposed treatment-based classification system for patients receiving physical therapy interventions for neck pain. Phys Ther.; 2007;87(5):513–24.

8 Cleland JA, Childs JD, Fritz JM, Whitman JM, Eberhart SL. Development of a Clinical Prediction Rule for Guiding Treatment of a Subgroup of Patients With Neck Pain: Use of Thoracic Spine Manipulation, Exercise, and Patient Education. Phys Ther. 2007;87(1):9–23.

193192

7

9 Schellingerhout JM, Verhagen AP, Heymans MW, Pool JJM, Vonk F, Koes BW, de Vet HCW. Which subgroups of patients with non-specific neck pain are more likely to benefit from spinal manipulation therapy, physiotherapy, or usual care? Pain. 2008;139(3):670–80.

10 Raney NH, Petersen EJ, Smith TA, Cowan JE, Rendeiro DG, Deyle GD, Childs JD. Development of a clinical prediction rule to identify patients with neck pain likely to benefit from cervical traction and exercise. Eur Spine J. 2009;18(3):382–91.

11 Holtermann A, Hansen JV, Burr H, Søgaard K. Prognostic factors for long-term sickness absence among employees with neck-shoulder and low-back pain. Scand J Work Environ Health. 2010;36(1):34–41.

12 Lakke SE, Soer R, Takken T, Reneman MF. Risk and prognostic factors for non-specific musculoskeletal pain: A synthesis of evidence from systematic reviews classified into ICF dimensions. Pain. 2009;147(1-3):153–64.

13 Hill JC, Lewis M, Sim J, Hay EM, Dziedzic K. Predictors of poor outcome in patients with neck pain treated by physical therapy. Clin J Pain. 2007;23(8):683–90.

14 Karels CH, Bierma-Zeinstra SMA, Burdorf A, Verhagen AP, Nauta AP, Koes BW. Social and psychological factors influenced the course of arm, neck and shoulder complaints. J Clin Epidemiol. 2007;60(8):839–48.

15 Lötters F, Burdorf A. Prognostic factors for duration of sickness absence due to musculoskeletal disorders. Clin J Pain. 2006;22(2):212–21.

7

16 Hill JC, Dunn KM, Lewis M, Mullis R, Main CJ, Foster NE, Hay EM. A primary care back pain screening tool: Identifying patient subgroups for initial treatment. Arthritis Rheum. 2008;59(5):632–41.

17 Azimi P, Shahzadi S, Azhari S, Montazeri A. A validation study of the Iranian version of STarT Back Screening Tool (SBST) in lumbar central canal stenosis patients. J Orthop Sci. 2013;19(2):213–7.

18 Bruyère O, , Demoulin M, Beaudart C, Hill JC, Maquet D, Genevay S, Mahieu G, Reginster JY, Crielaard JM, Demoulin C. Validity and Reliability of the French Version of the STarT Back Screening Tool for Patients With Low Back Pain. Spine. 2014;39(2):E123–8.

19 Morsø L, Albert H, Kent P, Manniche C, Hill J. Translation and discriminative validation of the STarT Back Screening Tool into Danish. Eur Spine J. 2011;20(12):2166–73.

20 Aebischer B, Hill JC, Hilfiker R, Karstens S. German Translation and Cross-Cultural Adaptation of the STarT Back Screening Tool. Montazeri A, editor. PLoS ONE. 2015;10(7):e0132068–14.

21 Karstens S, Krug K, Hill JC, Stock C, Steinhaeuser J, Szecsenyi J, Joos S.Validation of the German version of the STarT-Back Tool (STarT-G): a cohort study with patients from primary care practices. BMC Musculoskelet Disord. 2015;16:346.

22 Gusi N, del Pozo-Cruz B, Olivares PR, Hernández-Mocholi M, Hill JC. The Spanish version of the “STarT Back Screening Tool” (SBST) in different subgroups. Atención Primaria. 2011;43(7):356–61.

195194

7

23 Hill JC, Whitehurst DGW, Lewis M, Stirling B, PhD KMD, Foster NE, Konstantinou K, Main CJ, Mason E, Somerville S, Sowden G, Vohora K, HayEM. Comparison of stratified primary care management for low back pain with current best practice (STarT Back): a randomised controlled trial. The Lancet. 2011;378:1560–71.

24 Vonk F, Verhagen AP, Twisk JW, Köke AJA, Luiten MWCT, Koes BW. Effectiveness of a behaviour graded activity program versus conventional exercise for chronic neck pain patients. Eur J Pain. 2009;13(5):533–41.

25 Pool JJM, Ostelo RWJG, Knol DL, Vlaeyen JWS, Bouter LM, de Vet HCW. Is a behavioral graded activity program more effective than manual therapy in patients with subacute neck pain? Results of a randomized clinical trial. Spine. 2010;35(10):1017–24.

26 Groeneweg R, van Assen L, Kropman H, Leopold H, Mulder J, Smits-Engelsman BCM, Ostelo RWJG, Oostendorp RAB, van Tulder MW. The effectiveness of manual therapy and physical therapy in patients with non-specific neck pain: a Randomized Controlled Trial. Chiropractic & Manual Therapies. 2017;25:12 DOI 10.1186/s12998-017-0141-3

27 Vet HCW, Ostelo RWJG, Terwee CB, Roer N, Knol DL, Beckerman H, Boers M, Bouter LM. Minimally important change determined by a visual method integrating an anchor-based and a distribution-based approach. Qual Life Res. 2007;16(1):131–42.

28 Kamper SJ, Ostelo RWJG, Knol DL, Maher CG, de Vet HCW, Hancock MJ. Global Perceived Effect scales provided reliable assessments of health transition in people with musculoskeletal disorders, but ratings are strongly influenced by current status. J Clin Epidemiol. 2010;63(7):760–1

7

29 Bier JD, Scholten-Peeters GGM, Staal JB, Pool J, van Tulder M, Beekman E, Meerhoff GM, Knoop J, Verhagen AP. KNGF-richtlijn Nekpijn. Koninklijk Nederlands Genootschap voor Fysiotherapie (KNGF). (2016)

30 Vonk F, Verhagen AP, Geilen M, Vos CJ, Koes BW. Effectiveness of behavioural graded activity compared with physiotherapy treatment in chronic neck pain: design of a randomised clinical trial. BMC Musculoskelet Disord. 2004;5(1):34..

31 Pool JJM, Ostelo RWJG, Köke AJ, Bouter LM, de Vet HCW. Comparison of the effectiveness of a behavioural graded activity program and manual therapy in patients with sub-acute neck pain: Design of a randomized clinical trial. Man Ther. 2006;11(4):297–305.

32 Groeneweg R, Kropman H, Leopold H, van Assen L, Mulder J, van Tulder MW, Oostendorp RAB. The effectiveness and cost-evaluation of manual therapy and physical therapy in patients with sub-acute and chronic non specific neck pain. Rationale and design of a Randomized Controlled Trial (RCT). BMC Musculoskelet Disord. 2010;11(1):14.

33 Beneciuk JM, Bishop MD, Fritz JM, Robinson ME, Asal NR, Nisenzon AN, George SZ. The STarT Back Screening Tool and individual psychological measures: evaluation of prognostic capabilities for low back pain clinical outcomes in outpatient physical therapy settings. Phys Ther. 2013;93(3):321–33.

34 Field J, Newell D. Relationship between STarT Back Screening Tool and prognosis for low back pain patients receiving spinal manipulative therapy. Chiropr Man Therap. 2012;20:17.

194

7

35 Fritz JM, Beneciuk JM, George SZ. Relationship Between Categorization With the STarT Back Screening Tool and Prognosis for People Receiving Physical Therapy for Low Back Pain. Phys Ther. 2011;91(5):722–32.

36 Hill JC, Vohora K, Dunn KM, Main CJ, Hay EM. Comparing the STarT back screening tool’s subgroup allocation of individual patients with that of independent clinical experts. Clin J Pain. 2010;26(9):783–7.

37 Kongsted A, Andersen CH, Hansen MM, Hestbæk L. Prediction of outcome in patients with low back pain - A prospective cohort study comparing clinicians’ predictions with those of the Start Back Tool. Man Ther. 2015; 30:1–8.

38 Morsø L, Kent P, Manniche C, Albert HB. The predictive ability of the STarT Back Screening Tool in a Danish secondary care setting. Eur Spine J. 2014;23(1):120–8.

39 Newell D, Field J, Pollard D. Using the STarT Back Tool: Does timing of stratification matter? Man Ther. 2015;20(4):533–9.

40 Vernon H. The Neck Disability Index: state-of-the-art, 1991-2008. J Manipulative Physiol Ther. 2008;31(7):491–502.

41 Kato S, Takeshita K, Matsudaira K, Tonosu J, Hara N, Chikuda H. Normative score and cut-off value of the Neck Disability Index. J Orthop Sci. 2012;DOI 10.1007/s00776-012-0276-y.

42 Evans R, Bronfort G, Maiers M, Schulz C, Hartvigsen J. “I know it’s changed”: a mixed-methods study of the meaning of Global Perceived Effect in chronic neck pain patients. Eur Spine J. 2014;23(4):888 –97.