Articles

Development of the PHASES score for prediction of risk ofrupture of intracranial aneurysms: a pooled analysis of six
prospective cohort studies
Jacoba P Greving, Marieke J H Wermer, Robert D Brown Jr, Akio Morita, Seppo Juvela, Masahiro Yonekura, Toshihiro Ishibashi, James C Torner,
Takeo Nakayama, Gabriël J E Rinkel, Ale Algra

Summary
Background The decision of whether to treat incidental intracranial saccular aneurysms is complicated by limitations
in current knowledge of their natural history. We combined individual patient data from prospective cohort studies todetermine predictors of aneurysm rupture and to construct a risk prediction chart to estimate 5-year aneurysm
rupture risk by risk factor status.
Methods We did a systematic review and pooled analysis of individual patient data from 8382 participants in six
prospective cohort studies with subarachnoid haemorrhage as outcome. We analysed cumulative rupture rates with
Kaplan-Meier curves and assessed predictors with Cox proportional-hazard regression analysis.
Findings Rupture occurred in 230 patients during 29 166 person-years of follow-up. The mean observed 1-year risk ofaneurysm rupture was 1·4% (95% CI 1·1–1·6) and the 5-year risk was 3·4% (2·9–4·0). Predictors were age,
hypertension, history of subarachnoid haemorrhage, aneurysm size, aneurysm location, and geographical region. In
study populations from North America and European countries other than Finland, the estimated 5-year absolute riskof aneurysm rupture ranged from 0·25% in individuals younger than 70 years without vascular risk factors with asmall-sized (<7 mm) internal carotid artery aneurysm, to more than 15% in patients aged 70 years or older withhypertension, a history of subarachnoid haemorrhage, and a giant-sized (>20 mm) posterior circulation aneurysm. By
comparison with populations from North America and European countries other than Finland, Finnish people had a
3·6-times increased risk of aneurysm rupture and Japanese people a 2·8-times increased risk.
Interpretation The PHASES score is an easily applicable aid for prediction of the risk of rupture of incidental
intracranial aneurysms.
Funding Netherlands Organisation for Health Research and Development.

Introduction
Intracranial aneurysms occur in around 3% of the
population,1 which means around 15 million inhabitantsof the European Union have an unruptured intracranial
aneurysm. Owing to the rising availability of brain
imaging, the number of incidentally discovered
aneurysms is increasing.2 Rupture of intracranial
aneurysms results in aneurysmal subarachnoid
haemorrhage, a subset of stroke that has high casefatality and morbidity, and occurs at a relatively young
age compared with other types of stroke.3–5 In patientswith unruptured aneurysms, the decision whether totreat is often not straightforward. Preventive treatment
of intracranial aneurysms carries a risk of combined
treatment-related fatality and morbidity of up to
5%.6 Neurosurgical treatment has a higher risk ofcomplications than does endovascular treatment,7 but
the risk of rupture after endovascular treatment isslightly higher than after surgery, with annual rupture
rates of 0·2% according to a large systematic
review.6 The risks of treatment have to be balanced
carefully against the risk of rupture.8 However,prediction of the risk of rupture is diﬃcult.

Many prognostic factors for aneurysm rupture havebeen proposed.9 Risk factors for subarachnoid
haemorrhage include aneurysm size and aneurysm site,with higher risks for larger aneurysms and aneurysms in
the posterior circulation.10–14 Multiple aneurysms,12 female
sex,9 young age,11,12 history of subarachnoid haemorrhage,13 and cigarette smoking11 have been suggested asrisk factors in some studies, but not in others. Moreover,estimation of absolute risk of aneurysm rupture in apatient based on combination of risk factors is complex
and a clinical risk score for aneurysm rupture does notexist. Ideally, one would be able to calculate the risk ofaneurysm rupture on the basis of readily available datafor patient and aneurysm characteristics.
We undertook a pooled analysis of individual patient
data from prospective cohort studies in which data werereported for the natural history of unruptured aneurysms
and risk factors predicting rupture. The aim was toestablish predictors of aneurysm rupture in patients with
unruptured intracranial aneurysms and to provide a risk
prediction chart that allows physicians to easily determine
the 5-year risk of aneurysm rupture on the basis of a set ofroutinely assessed patient and aneurysm characteristics.

www.thelancet.com/neurology Published online November 27, 2013 http://dx.doi.org/10.1016/S1474-4422(13)70263-1

Published Online
November 27, 2013
http://dx.doi.org/10.1016/
S1474-4422(13)70263-1
See Online/Comment
http://dx.doi.org/10.1016/
S1474-4422(13)70272-2
Julius Center for Health Sciences
and Primary Care, University
Medical Center Utrecht,
Utrecht, Netherlands(J P Greving PhD,Prof A Algra MD); Department of
Neurology, Leiden University
Medical Center, Leiden,
Netherlands (M J H Wermer MD);
Department of Neurology,
Mayo Clinic, Rochester, MN,
USA (Prof R D Brown Jr MD);UCAS Japan CoordinatingOﬃce, University of Tokyo,
Tokyo, Japan (Prof A Morita MD);
Department of Neurological
Surgery, Nippon Medical
School, Tokyo, Japan(Prof A Morita); Department ofClinical Neurosciences,
University of Helsinki, Helsinki,
Finland (S Juvela MD);
Department of Neurosurgery,
National Nagasaki Medical
Center, Nagasaki, Japan(M Yonekura MD); Division ofEndovascular Neurosurgery,Tokyo Jikei University School of
Medicine, Tokyo, Japan(T Ishibashi MD); Department of
Epidemiology, University of
Iowa, Iowa City, IA, USA(Prof J C Torner PhD);
Department of Health
Informatics, Kyoto University
School of Public Health, Kyoto,
Japan (Prof T Nakayama MD);and Department of Neurology
and Neurosurgery, Brain Center
Rudolf Magnus, University
Medical Center Utrecht,
Utrecht, Netherlands(Prof G J E Rinkel MD,
Prof A Algra)
Correspondence to:
Dr Jacoba P Greving, Julius Centerfor Health Sciences and Primary
Care, University Medical CenterUtrecht, PO Box 85500,
3508 GA Utrecht, Netherlands
j.p.greving@umcutrecht.nl

1Articles

Methods
Search strategy and selection criteria

See Online for appendix

We did a systematic search in PubMed and Embase, up
to July 25, 2013, to retrieve all relevant studies on riskof rupture of unruptured aneurysms. In brief, we used
the keywords “(intracranial aneurysm(s) OR cerebral
aneurysm(s)) AND (risk of rupture OR aneurysm rupture
OR risk factors OR rupture OR unruptured OR
subarachnoid hemorrhage) AND (follow-up OR natural
history OR natural course)” (appendix). We selectedstudies that: (1) included 50 or more patients with
unruptured intracranial aneurysms, (2) studied thenatural course of unruptured intracranial aneurysms
and studied risk factors for aneurysm rupture, (3) used aprospective study design, and (4) had aneurysm rupture(aneurysmal subarachnoid haemorrhage) as an outcome.
852 publications identiﬁed
through PubMed

989 publications identiﬁed
through Embase

736 duplicate publications

1105 publications screenedon basis of title andabstract

1003 excluded
541 treatment study
145 ruptured aneurysms
140 case report or review
68 high-risk populations
38 diagnostic study
23 modelling study
24 aneurysm rupture notan outcome
24 other (genetic study,
animal study, survey)

102 manuscripts reviewed

73 excluded
31 review or editorial
27 retrospective
ascertainment of data
6 no full-text available
9 other (simulation study,
case-control study, study
population <50 patients)

29 publications judged eligible
for inclusion in the IPD

23 excluded
22 multiple publications
1 IPD not available

6 publications included in the IPD

Figure 1: Flowchart
IPD=individual patient data.

2

There were no date or language restrictions other than
the requirement for an abstract in English in case offoreign language journals.
One author (JPG) checked the titles and abstracts of theidentiﬁed publications to select studies potentially meeting
the inclusion criteria. Two authors (JPG and MJHW)
independently reviewed full-text copies of the selectedpublications to decide which met the inclusion criteria. Of
1105 potentially relevant publications, 102 were retrieved
for more detailed evaluation (ﬁgure 1). 29 publications(based on seven diﬀerent cohort studies) met our inclusion
criteria. Of the seven eligible cohorts, six research groups
provided us with their individual patient data;10–15 for one
cohort on 111 patients we could not retrieve data.16

Study populations
The International Study of Unruptured Intracranial
Aneurysms (ISUIA) is a large multicentre, prospective
cohort study done in 60 centres in the USA, Canada, andEurope.10 The cohort without aneurysm treatment
included 1691 patients who were included between
1991 and 1998 and were followed up annually with theuse of a standardised questionnaire. Patients were
eligible for enrolment if they could care for themselves(modiﬁed Rankin scale <3). Patients could undergo
surgical clipping or endovascular intervention at theinvestigator’s discretion.
In Finland, 142 patients with 181 unruptured
intracranial aneurysms were diagnosed between
1956 and 1978 and followed up thereafter.11 In this longterm, single-institution cohort study, most (92%)
patients harboured additional aneurysms discovered in
the diagnostic work-up of another ruptured aneurysm.
Follow-up evaluation was accomplished primarily byquestionnaires ﬁlled in during telephone interviews
with the patients or close relatives every
10 years.11,17–20 Information about all patients was alsoacquired from the medical records of other hospitals
and general practitioners to corroborate the accuracy ofthe data concerning diseases, medicines, and bloodpressure. Autopsy reports and oﬃcial death certiﬁcatesof the patients were examined. Patients did not undergo
surgical clipping or endovascular treatment during theﬁrst 25 years of follow-up.
The Small Unruptured Aneurysm Veriﬁcation Study(SUAVe study) is a multicentre, prospective study done by
12 centres in Japan.12 The baseline examination (between
2000 and 2004) included 374 patients. All incidentallyfound unruptured saccular aneurysms less than 5 mm indiameter were registered and followed up at 6, 12, 18, 24,
30, and 36 months and yearly thereafter. All patients wereinterviewed by contributors to the study, at eachparticipating centre, who ﬁlled out a structured checklist.
Patients could undergo surgical clipping or endovascularintervention at the investigator’s discretion, if aneurysms
enlarged by 2 mm or more in diameter or developed ableb during the course of observation.

www.thelancet.com/neurology Published online November 27, 2013 http://dx.doi.org/10.1016/S1474-4422(13)70263-1

Articles

In Japan, 703 patients with 889 unruptured intracranial
aneurysms were referred to one centre between 2003 and2006.13 Patients with fusiform or dissecting aneurysms andpatients with less than 6 months’ follow-up were excluded(102 patients with 118 unruptured intracranial aneurysms).
Patients with aneurysms larger than 5 mm were regarded
as potential candidates for treatment; 242 aneurysms weretreated. The remaining 419 patients with 529 aneurysms
elected conservative management, and CT angiography
follow-up was obtained every 6 months.
In the Netherlands, a short-term clinical andradiological follow-up study was done by two centres inpatients with a history of subarachnoid haemorrhage orfamilial intracranial aneurysms in whom an aneurysm of
5 mm or smaller was detected at screening but nottreated.15 The baseline examination (between 2002 and2004) included 93 patients. Follow-up CT or MR
angiography was done after 1 year. Patients did notundergo surgical clipping or endovascular treatment.
The Unruptured Cerebral Aneurysm Study of Japan(UCAS Japan) is a large, multicentre, prospective cohort
study.14 The baseline examination (between 2001 and2004) included 5720 patients with newly identiﬁed,
unruptured saccular aneurysms 3 mm or larger indiameter. Follow-up data for patients’ clinical status wererecorded through either direct interview or telephone
contact at 3, 12, and 36 months and yearly thereafter.
Patients could undergo surgical clipping or endovascularintervention at the investigator’s discretion.
The general characteristics of the six cohort studies
included in the pooled analysis are reported in table 1 andthe appendix. 57 patients who were included in both
SUAVe and UCAS were excluded from the SUAVe
cohort, leaving 8382 patients for analysis.

Data collection
The data requested for each patient included the following
at baseline: date of inclusion, age, sex, history ofsubarachnoid haemorrhage, smoking status, hypertension

status (deﬁned as systolic blood pressure >140 mm Hg or
diastolic blood pressure >90 mm Hg or use of antihypertensive drugs), number of aneurysms, maximum diameterof aneurysms, aneurysm location; and during follow-up:
occurrence of a rupture, date of occurrence, date of asurgical or endovascular intervention, date of death, dateof last follow-up assessment, and whether the patient waslost to follow-up. All data were thoroughly checked for consistency (logical checking and checking against the original
publications). A few issues were queried with the responsible investigator or statistician, and all were resolved.
We classiﬁed the location of the aneurysm as theinternal carotid artery, posterior communicating artery,anterior cerebral arteries (including the anterior cerebral
artery, anterior communicating artery, and pericallosalartery), middle cerebral artery, or posterior circulation(including the vertebral artery, basilar artery, cerebellar
arteries, and posterior cerebral artery).

Statistical analysis
Information was available for 98% of the potential
predictors (range 93–100%) and for 100% of the outcome
measure. Missing data were imputed for smoking,hypertension, and aneurysm location within each cohort
with the linear regression method (multivariable
analyses) available in SPSS. One study did not provide
data for smoking and hypertension.13 To assign values forthese missing data, we did single imputation using all
relevant prognostic factors and outcome from the pooled
dataset. A sensitivity analysis was done by excluding
participants for whom data were missing.
Follow-up data for patients were censored at the time ofan aneurysm rupture, death, the last follow-up assessment,
or at the time of surgical or endovascular aneurysm
treatment. We analysed rupture risk per patient. When apatient had multiple aneurysms, the largest of theseaneurysms, along with its location, served to categorise
the patient. Additionally, we did an aneurysm-based
analysis. Kaplan-Meier curves were used to examine theCountry

Recruitment
periodInclusion criteria

Imaging used to assess
initial aneurysm
characteristics

Number of Mean age
patients(range; years)

Number of Patients
Patients with a Median
SAHs during treated duringhistory of SAH follow-up
follow-up(range; years) follow-up

ISUIA10

USA, Canada,
and Europe

1991–98

Saccular aneurysm≥2 mm, mRS <3

Conventional angiography1691

55 (10–90)

615 (36%)

9·0 (0–15)

59

534 (32%)

Juvela et al11

Finland

1956–78

Non-fusiform, non- Conventional angiography
mycotic aneurysm142

41 (14–60)

131 (92%)

21·0 (0–52)

34

3 (2%)*

SUAVe study12

Japan

2000–04

Saccular aneurysm≤5 mm, mRS <3

MRA, CTA, DSA

374

62 (23–90)

36 (10%)3·2 (0–20)

7

10 (3%)

Ishibashi et al13 Japan

2003–06

Saccular aneurysm

CTA

419

60 (17–86)

14 (3%)

2·1 (0–22)†

19

0

Wermer et al15

Netherlands

2002–04

Non-fusiform
aneurysm ≤5 mm

CTA, DSA

93

50 (19–69)

77 (83%)2·2 (0–15)†

1

0

UCAS14Japan

2001–04

Saccular aneurysm≥3 mm, mRS <3

MRA, CTA, DSA,
conventional angiography

5720

63 (23–98)

187 (3%)

1·0 (0–9)

1112722 (48%)

SAH=subarachnoid haemorrhage. mRS=modiﬁed Rankin scale. MRA=magnetic resonance angiography. CTA=CT angiography. DSA=digital subtraction angiography. *Three patients were treated after follow-ups
of 24·4–25·9 years. †These prospective cohort studies included a retrospective component, in case an aneurysm was already present before the start of follow-up (Ishibashi et al,13 n=17; Wermer et al,15 n=40).

Table 1: Cohort studies of untreated unruptured aneurysms included in our pooled analysis

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3

Articles

5-year absolute risk of aneurysm rupture for each potential
predictor. Restricted cubic spline functions and graphs
were used to establish whether continuous variables (age,aneurysm size) could be analysed as linear terms orneeded transformation.21 An age-squared term was foundto be signiﬁcant in the prediction model. Predictors ofaneurysm rupture were studied with Cox proportional
hazard regression models with stratiﬁcation for cohort.
Predictors were considered for entrance in themultivariable regression model irrespective of theirunivariable association with aneurysm rupture. The fullmodel was simpliﬁed with a backward selection procedure(exclusion if p>0·20). We visually inspected the log minus
log plot for each predictor and detected no deviations from
Rupture(n=220)No rupture(n=8162)

161 (73%)5530 (68%)<40 years

26 (12%)406 (5%)40–49 years

24 (11%)982 (12%)50–59 years

34 (15%)2205 (27%)

60–69 years

55 (25%)2656 (33%)≥70 years

81 (37%)

1913 (23%)

Hypertension

115 (52%)3522 (43%)

Female sex

Ever smoker

76 (35%)2621 (32%)

AgePrevious SAH

50 (23%)1010 (12%)

Patient characteristics
Women
Age

Number of aneurysms

Univariable

Multivariable*

1·2 (0·9–1·7)··

Age (per 5 years)

0·6 (0·4–0·7)

0·7 (0·5–0·9)

Age squared

1·0 (1·0–1·0)

1·0 (1·0–1·0)

1·6 (1·2–2·0)

1·4 (1·1–1·8)

Single167 (76%)6722 (82%)

Hypertension

Multiple

53 (24%)1440 (18%)

Ever smoking

0·6 (0·4–0·8)··

Previous SAH from other aneurysm

0·7 (0·5–1·0)

1·4 (0·9–2·2)

Multiple aneurysms

1·3 (0·9–1·7)··

Geographical region
North America and European
countries other than Finland

57 (26%)1695 (21%)

Japan

129 (59%)

6327 (78%)<5·0 mm

Reference

Finland34 (15%)140 (2%)

5·0–6·9 mm

1·1 (0·7–1·7)

1·1 (0·7–1·7)

7·0–9·9 mm

2·7 (1·8–4·0)

2·4 (1·6–3·6)

10·0–19·9 mm

5·3 (3·7–7·7)

5·7 (3·9–8·3)≥20·0 mm14·3 (9·4–21·8) 21·3 (13·5–33·8)Size of aneurysm

Aneurysm characteristics*
Size at time of detection<5·0 mm

Reference57 (26%)3839 (47%)

5·0–6·9 mm

27 (12%)2099 (26%)

7·0–9·9 mm

38 (17%)1213 (15%)

Anterior cerebral arteries

1·6 (1·1–2·5)

1·7 (1·1–2·6)

10·0–19·9 mm

62 (28%)851 (10%)

Internal carotid artery

0·6 (0·4–0·9)

0·5 (0·3–0·9)≥20·0 mm

36 (16%)160 (2%)

Posterior communicating artery

2·4 (1·7–3·5)

2·1 (1·4–3·0)

Middle cerebral artery

Reference

Reference

2·5 (1·6–3·7)

1·9 (1·2–2·9)

Location

Aneurysm location

Anterior cerebral arteries

41 (19%)1525 (19%)

Posterior arteries

Internal carotid artery

83 (38%)3091 (38%)

Geographical region

Posterior communicating artery

56 (25%)1185 (15%)

Reference

27 (12%)1906 (23%)

North America and European
countries other than Finland

Reference

Other internal carotid artery
Middle cerebral artery

54 (25%)2773 (34%)

Japan

2·0 (1·4–2·9)

2·8 (1·8–4·2)

Posterior circulation

42 (19%)773 (9%)Finland

2·4 (1·5–4·1)

3·6 (2·0–6·3)

Data are n (%). Ten patients with rupture of an aneurysm that was not the largest
are included in the reference group (no rupture). SAH=subarachnoid
haemorrhage. *Aneurysm size and location of the largest unruptured aneurysm at
the time of aneurysm detection are shown.

Table 2: Baseline characteristics of all patients in the six cohorts

4

the assumption of proportional hazards. Model performance was examined by determination of the model’s
discrimination and calibration. Discrimination of themodel, which is expressed as a concordance (c) statistic,
indicates to what extent the model distinguishes between
patients who do and do not rupture during follow-up. Thec statistic has a theoretical range between 0·5 and 1·0, but
it typically ranges from 0·60 to 0·85 for prognostic
models.21 Calibration is the agreement between thepredicted risks and the observed risks of rupture and wasassessed with the calibration plot and Grønnesby andBorgan test.22
Prognostic models derived from multivariable
regression analysis are known to overestimate regression
coeﬃcients, which results in overestimated predictions
when applied in new patients.23,24 Therefore, we internallyvalidated our model with bootstrapping techniques, andthe entire modelling process was repeated in eachbootstrap sample.24 A shrinkage factor was estimated fromthe bootstrap validation procedure and we shrank theregression coeﬃcients to provide improved predictions
for future patients.23 The bootstrap procedure was also
used to estimate the c statistic corrected for overoptimism.

Data are hazard ratio (95% CI). SAH=subarachnoid haemorrhage. *The initial
regression coeﬃcients were adjusted for overﬁtting with a shrinkage factor of 0·95.

Table 3: Univariable and multivariable Cox regression analysis of predictorsof aneurysm rupture risk in patients with unruptured intracranial
aneurysms from the pooled data from six cohorts

www.thelancet.com/neurology Published online November 27, 2013 http://dx.doi.org/10.1016/S1474-4422(13)70263-1

Articles

We derived the 5-year aneurysm rupture risk for anindividual patient with a given risk factor status by applying
the hazard ratios to the pooled data (appendix). A risk
prediction chart was generated on the basis of the
combination of risk factor levels and the corresponding
risk of 5-year aneurysm rupture. All subgroups with anestimated 5-year risk greater than 15% were categorised asvery high risk (>15%), since our risk prediction modeltends to overestimate risk in these small subgroups (4% of
the population). Additionally, we presented a risk scorewith scores based on the regression coeﬃcients in the ﬁnal
Cox proportional hazards model.25 Analyses were done withIBM SPSS Statistics (version 20.0) and R 2.15.2 software.

Role of the funding source
The sponsor of the study had no role in study design,
data collection, data analysis, data interpretation, or
writing of the report. The corresponding author had fullaccess to all the data in the study and had ﬁnal
responsibility for the decision to submit for publication.

Results
Table 2 shows the baseline characteristics of the8382 patients with 10 272 unruptured intracranial
aneurysms from the six cohort studies that were includedin the pooled analysis. Mean age was 60 years (SD 12)
and 68% of the patients were women. Rupture occurred

A Populations from North America and European countries other than Finland
No hypertension, no history of SAH

Hypertension, no history of SAH

Both hypertension and history of SAH

Aneurysm location

Aneurysm location

Aneurysm location

ICA

MCA

ACA

Pcom/
posterior≥20 mm

7

13

>15

>15

10·0–19·9 mm

2

4

6

7

7·0–9·9 mm

1

1

3

<7 mm

0

1

Size

ICA

≥20 mm5Size

10·0–19·9 mm

ACA

Pcom/
posterior

10

>15

>15

>15

3

5

8

9

3

1

2

3

1

1

0

1

MCA

ACA

Pcom/
posterior

ICA

9

15

>15

7

0

5

4

0

≥70 years

Age<70 years

2

2

1

1

<7 mm

MCA

2

1

7·0–9·9 mm

ICA

Age

MCA

ACA

Pcom/
posterior

14

>15

>15

>15

4

7

11

13

4

2

3

5

6

1

2

1

1

2

3

MCA

ACA

Pcom/
posterior

ICA

MCA

ACA

Pcom/
posterior

12

>15

>15

10

>15

>15

>15

6

7

3

5

8

9

2

3

1

2

3

4

1

1

0

1

2

2

3

2

1

1

1

1

ICA

0

1

Age

≥70 years

Age<70 years

B Japanese population
No hypertension, no history of SAH

Hypertension, no history of SAH

Both hypertension and history of SAH

Aneurysm location

Aneurysm location

Aneurysm location

Size

ICA

MCA

ACA

Pcom/
posterior≥20 mm

Age

ICA

MCA

ACA

Pcom/
posterior

Age

ICA

MCA

ACA

Pcom/
posterior

>15

>15

>15

>15

>15

>15

>15

>15

>15

>15

>15

>15

10·0–19·9 mm

5

10

>15

>15

7

13

>15

>15

10

>15

>15

>15

7·0–9·9 mm

2

4

7

8

3

5

9

11

4

8

13

15

<7 mm

1

2

3

4

1

2

4

5

2

3

6

7

Size

ICA

MCA

ACA

Pcom/
posterior

ICA

MCA

ACA

Pcom/
posterior

ICA

MCA

ACA

Pcom/
posterior≥20 mm

13

>15

>15

>15

>15

>15

>15

>15

>15

>15

>15

>15

10·0–19·9 mm

4

7

11

13

5

9

15

>15

7

13

>15

>15

7·0–9·9 mm

2

3

5

6

2

4

6

8

3

5

9

11

<7 mm

1

1

2

3

1

2

3

3

1

2

4

5

≥70 years

Age<70 years≥70 years

Age<70 years

High risk
Intermediate risk
Low risk
Very low risk

Figure 2: Risk prediction charts for aneurysm rupture(A) Populations from North America and European countries other than Finland. (B) Japanese population. The number in each cell refers to the predicted risk (%) for
aneurysm rupture within the next 5 years. Colour coding refers to the risk of rupture, not to the trade-oﬀ between the risk of rupture and risk of treatment.
ICA=internal carotid artery. MCA=middle cerebral artery. ACA=anterior cerebral arteries (including the anterior cerebral artery, anterior communicating artery, andpericallosal artery). Pcom=posterior communicating artery. posterior=posterior circulation (including the vertebral artery, basilar artery, cerebellar arteries, andposterior cerebral artery). SAH=subarachnoid haemorrhage.

www.thelancet.com/neurology Published online November 27, 2013 http://dx.doi.org/10.1016/S1474-4422(13)70263-1

5

Articlesin 230 patients during 29 166 person-years of follow-up(median 2·9 years; range 0–52 years); in 220 patients, asingle or the largest aneurysm ruptured. The observed
1-year risk of aneurysm rupture was 1·4% (95% CI
1·1–1·6) and the 5-year risk was 3·4% (2·9–4·0). The
Kaplan-Meier curve showed that the rate of rupture
decreased during the ﬁrst 5 years of follow-up (appendix).
Table 3 presents the results from a multivariable Cox
proportional hazards model. Age, hypertension, historyof subarachnoid haemorrhage, aneurysm size, aneurysm
location, and geographical region were independent
predictors of aneurysm rupture. Sex, smoking atbaseline, and presence of multiple aneurysms were
excluded from the model, because of their limited
predictive value (p>0·20). After shrinkage of thecoeﬃcients, the c statistic of the ﬁnal model was 0·82
(95% CI 0·79–0·85). The Grønnesby and Borgan test was
not signiﬁcant (p=0·07), indicating a good overall ﬁt(appendix). We visually inspected the log minus log plot
for each predictor and detected no deviations from the

PHASES aneurysm risk score

Points(P) Population
North American, European (other than Finnish)

0Japanese

3

Finnish5(H) Hypertension
No

0

Yes

1

(A) Age<70 years

0≥70 years

1(S) Size of aneurysm<7·0 mm07·0–9·9 mm

3

10·0–19·9 mm

6≥20 mm

10(E) Earlier SAH from another aneurysm
No

0

Yes

1

(S) Site of aneurysm
ICA

0

MCA

2

ACA/Pcom/posterior

4

To calculate the PHASES risk score for an individual, the number of points
associated with each indicator can be added up to obtain the total risk score. For
example, a 55-year-old North American man with no hypertension, no previous
SAH, and a medium-sized (8 mm) posterior circulation aneurysm will have a risk
score of 0+0+0+3+0+4=7 points. According to ﬁgure 3, this score corresponds toa 5-year risk of rupture of 2·4%. SAH=subarachnoid haemorrhage. ICA=internal
carotid artery. MCA=middle cerebral artery. ACA=anterior cerebral arteries(including the anterior cerebral artery, anterior communicating artery, andpericallosal artery). Pcom=posterior communicating artery. posterior=posterior
circulation (including the vertebral artery, basilar artery, cerebellar arteries, andposterior cerebral artery).

Table 4: Predictors composing the PHASES aneurysm rupture risk score

6

assumption of proportional hazards. As a sensitivity
analysis, we did all analyses in a subset of data with no
missing covariate data for hypertension and aneurysm
location (n=7776) and found similar results. Additionally,
we did an aneurysm-based analysis and the results were
essentially the same.
Figure 2 shows the risk charts. In study populations
from North America and European countries other thanFinland, the predicted 5-year absolute risk of aneurysm
rupture ranged from 0·25% in individuals younger than
70 years without vascular risk factors and with a smallsized (<7 mm) internal carotid artery aneurysm to morethan 15% in individuals aged 70 years or older withhypertension, a history of subarachnoid haemorrhage,
and a posterior circulation aneurysm of giant size(>20 mm). By comparison with populations from North
America and European countries other than Finland,
Finnish people had a 3·6-times increased risk ofaneurysm rupture and Japanese people a 2·8-times
increased risk. The formulae and coeﬃcients are shownin the appendix. A simple risk score, PHASES, ispresented in table 4, which can be used in combination
with ﬁgure 3 to obtain approximate predictions forindividual patients.

Discussion
We have developed a practical risk score (PHASES) thatpredicts a patient’s risk of aneurysm rupture on the basisof a set of routinely assessed patient and aneurysm
characteristics. We found that the largest amount ofprognostic information was contained in six predictors:
age, hypertension, history of subarachnoid haemorrhage,aneurysm size, aneurysm location, and geographicalregion. Sex, smoking status at time of aneurysm
detection, and presence of multiple aneurysms had noimportant eﬀect on the risk of rupture.
Reliable identiﬁcation of prognostic factors foraneurysm rupture has been diﬃcult, because the numberof aneurysm ruptures during follow-up in mostindividual studies was too small for valid analyses.10–13 By
reanalysing data from six prospective cohort studies, wewere able to include 8382 patients, of whom 230 had asubarachnoid haemorrhage during follow-up. This large
number of haemorrhages enabled us to undertake
multivariable analyses. To our knowledge, this study is
the ﬁrst to attempt to reliably predict the risk of aneurysm
rupture for an individual patient on the basis of a set of
easily available patient and aneurysm characteristics.
Obviously, risk scores will be more reliable if they
include predictors that are already well established risk
factors for aneurysm rupture. Aneurysm size andaneurysm location are such risk factors.10–14 We found that
sex, presence of multiple aneurysms, and smoking status
had no added value for the prediction of aneurysm
rupture when other risk factors were accounted for. Thisﬁnding does not mean that these factors are notimportant risk factors for aneurysm rupture in isolation,

www.thelancet.com/neurology Published online November 27, 2013 http://dx.doi.org/10.1016/S1474-4422(13)70263-1

Articles

20
18
16
Predicted probability of aneurysm rupture (%)

but, instead, these factors have no added value to theprediction of aneurysm rupture beyond the six predictors
used in our risk score. Importantly, for smoking status
we only had data for smoking at the time of aneurysm
detection, and not for smoking status during follow-up(except for one cohort study11). The absence of a risk
eﬀect of smoking on aneurysmal rupture might therefore
be accounted for by a change in smoking status after
aneurysm detection. Moreover, our data should not beinterpreted as a neutral eﬀect of continued smoking
during follow-up on risk of rupture. Similarly, we do nothave data for blood pressure management during followup, so no conclusions can be drawn about presence orabsence of high blood pressure during follow-up on riskof rupture. Other factors might predict aneurysm
rupture, such as family history of subarachnoid
haemorrhage26 or aneurysm growth,27 but these factors
were not consistently available in our studies. Moreover,growth can only be measured during follow-up and istherefore not a characteristic available at baseline.
Our study has some limitations. First, we did patientlevel analyses, and in patients with multiple aneurysms
we used only the characteristics of the largest unruptured
aneurysm in the analysis. Nevertheless, in the case ofaneurysm rupture during follow-up, in all but ten
patients the largest aneurysm ruptured. Second, somevalues were missing in our database. Regression
imputation was used to predict missing values withinformation from all potential predictors and outcome.
Both theoretical and empirical support is growing for theuse of imputation methods instead of traditional
complete case analysis.28 We repeated all analyses in a
subset of data with no missing covariables for
hypertension and aneurysm location and found similar
results. Third, although this model has been validated
internally, it has not yet been validated externally inanother population. However, this validation is currently
impossible to achieve because we captured almost all
published data for aneurysm rupture that are available
worldwide. Fourth, diﬀerent imaging modalities wereused to assess the initial aneurysm characteristics anddiﬀerent methods of measuring aneurysm size wereused across studies. Fifth, although the follow-up in mostcohorts was accurate, instances of subarachnoid haemorrhage might have been missed or the aneurysm listed as
the cause of the haemorrhage might have been incorrect.
Such misclassiﬁcation might have resulted in lessaccurate predictions and the overall risk of rupture might
be higher if haemorrhages have been missed. Sixth, apotential for selection bias exists in this study. For
example, in ISUIA and UCAS Japan many patients
received treatment during follow-up. Some patientsmight have received treatment because of an increase inaneurysm size or the development of new symptoms,
both of which are associated with increases in rupture
rate. Therefore, patients with aneurysms that might havebeen likely to rupture were removed from the cohort,

14
12

PHASESrisk scoren5-year risk ofaneurysm rupture

≤2
3
4
5
6
7
8
9
10
11
≥12

429
779
543
982
1078
1315
1118
625
388
384
736

0·4 (0·1–1·5)
0·7 (0·2–1·5)
0·9 (0·3–2·0)
1·3 (0·8–2·4)
1·7 (1·1–2·7)
2·4 (1·6–3·3)
3·2 (2·3–4·4)
4·3 (2·9–6·1)
5·3 (3·5–8·0)
7·2 (5·0–10·2)
17·8 (15·2–20·7)

10
8
6
4
2
0
≤2

3

4

5

6
7
PHASES risk score

8

9

10

11

≥12

Figure 3: Predicted 5-year risk of aneurysm rupture according to PHASES score

despite the original intent to treat conservatively. Thesetypes of selection bias deﬁnitely aﬀected the calculationof the risk of rupture. However, a pure natural history
study is now impossible to undertake. Only the Finnishcohort was recruited during a period when unruptured
aneurysms were not treated, and these patients were notoperated on during the ﬁrst 25 years of follow-up.11 Thisfactor might explain partly the increased rupture rate in
the Finnish cohort. However, incidence of subarachnoid
haemorrhage is higher in Finland than in other westerncountries and is probably caused by increased risk ofaneurysm rupture.19 Finally, the prediction holds true
only for the ﬁrst 5 years after aneurysm detection. Thisrisk cannot be extrapolated over the patients’ remaining
lifetime, because risk of aneurysm growth and rupture
are not constant over time.29
An important strength of our study is the large numberof patients with an unruptured intracranial aneurysm
from which the model was derived. Second, the natural
history studies took place in several diﬀerent countries,
improving external validity. Third, all included studies
were prospective cohort studies with careful follow-up.
Fourth, the predictors in our model are well deﬁned,
easily measured clinical variables. Furthermore, bothpatients with previous subarachnoid haemorrhage fromanother aneurysm and patients with incidentally foundaneurysms were included. Therefore, our risk chartseems to have broad applicability in prediction ofaneurysm rupture in various populations.
Our proposed risk prediction chart, based on easily
available patient and aneurysm characteristics, could

www.thelancet.com/neurology Published online November 27, 2013 http://dx.doi.org/10.1016/S1474-4422(13)70263-1

7

Articles

support physicians in their assessment of the risk ofaneurysm rupture and serve as a valuable aid in theclinical decision as to whether preventive occlusion of
the aneurysm is warranted. Further studies are neededon validation of the score, improved prediction of risks ofsurgical and endovascular treatment for an individual
patient, and risk of aneurysmal rupture beyond the ﬁrst
5 years after detection. The current risk prediction chart
provides the physician and the patient with a goodstarting point for discussing the pros and cons of thetherapeutic options.
Contributors
JPG, MJHW, GJER, and AA were involved in the design of the study.
RDB, JCT, AM, TN, SJ, MY, TI, MJHW, and GJER collected data. JPG
and AA were involved in the statistical analyses. JPG drafted the paper,and all authors reviewed and commented on the report.
Conﬂicts of interest
We declare that we have no conﬂicts of interest.
Acknowledgments
We thank all participating study groups for their willingness to share
their data in this project. This study was supported by an unconditional
grant from the Netherlands Organisation for Health Research andDevelopment (ZonMw, project number 120630031).
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