J O U R N A L O F G E R I A T R I C O N C O L O G Y 1 ( 2 0 1 0 ) 3 2 – 3 9

ava i l ab l e a t www.sc i enced i r ec t . com

Falls in men on androgen deprivation therapy forprostate cancer

Shabbir Hussaina, Henriette Breunisa, Narhari Timilshinaa, Shabbir M.H. Alibhaia,b,c,d,⁎a Department of Medicine, University Health Network, Toronto, Canadab Department of Medicine, University of Toronto, Toronto, Canadac Department of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canadad Research program, Toronto Rehabilitation Institute, Toronto, Canada

A R T I C L E I N F O

⁎ Corresponding author. University Health NeE-mail address: shabbir.alibhai@uhn.on.c

1879-4068/$ – see front matter © 2010 Elsevidoi:10.1016/j.jgo.2010.03.004

A B S T R A C T

Article history:Received 23 March 2010Accepted 24 March 2010

Objective: Androgen deprivation therapy (ADT) is a common treatment for prostate cancer(PC). However, it may increase the risk of falls due to decreases in testosterone, lean bodymass and strength. Falls are a leading cause of morbidity and mortality in older adults.However, the impact of ADT on falls remains unclear.Materials and methods: Three groups matched on age and education were recruited: PCpatients starting continuous ADT (ADT users) (n=88), PC patients not receiving ADT (PCcontrols) (n=86), and healthy controls (n=86). Patients retrospectively reported any falls inthe 12 months prior to study entry and prospectively at 3 time points over the next12 months (after starting ADT). Physical performance measures were done at each timepoint. The risks of having a fall at both baseline and over 1 year of follow-up were analyzedusing logistic regression.Result: At baseline 13.8% (n=36) of patients (ADT users=14.7%, PC controls=8.1%, healthycontrols=18.6%, p=0.132) reported falls in the prior year. In the multivariable model, TimedUp and Go, marital status and working status predicted fall risk at baseline. Over 12 months,24.8% (n=62) of patients (ADT users=34.5%, PC controls=18.1%, healthy controls=21.7%,p=0.035) reported falls. Prior history of falls, being unmarried and arthritis wereindependent predictors of falls whereas ADT use was borderline (p=0.08).Conclusion:ADT usemay be associatedwith an increased risk of falls, but larger confirmatorystudies are needed. Additionally, multiple non-physical factors including prior history offalls and arthritis predict future falls in older men on ADT.

© 2010 Elsevier Ltd. All rights reserved.

Keywords:Androgen deprivationFallsProstate cancerMenAged

1

1. Background

Prostate cancer is the most common non-skin cancer and thesecond most common cause of cancer mortality in Americanmen,with 1out of every 6mendeveloping it in their lifetime. 75%of prostate cancer incident cases andmore than 90% of prostate

twork, 200 Elizabeth St Ra (S.M.H. Alibhai).

er Ltd. All rights reserved

cancer deaths occur inmen aged >65 years . Prostate cancer hasbeen recognized as an androgen-sensitive disease since theseminal work of Huggins and Hodges in 194142. Indications forandrogen deprivation therapy (ADT) have expanded over theyears. As such, ADT is now used in patients as primary therapyfor localized cancer2, with locally advanced disease3, withbiochemical relapse4, and with metastatic disease5.

oom EN14-214, Toronto, Ontario, Canada, M5G 2C4.

.

33J O U R N A L O F G E R I A T R I C O N C O L O G Y 1 ( 2 0 1 0 ) 3 2 – 3 9

1.1. ADT side effects

Low testosterone induced by ADT is associated with gyneco-mastia, weight gain, decreased libido, anemia, fatigue, de-pression, decreased muscle mass, decreased bone mineraldensity, and possibly an increased risk of falls6,7.

Testosterone and dihydrotestosterone (DHT) are the twomajor androgens in men, with testosterone present mainly incirculation, and DHT the primary androgen in prostatic tissues.As ADT is given to patients, it leads to decreases in testosteronelevelwith commensurate slowing of the progression of prostatecancer. Although several prior studies have reported that lowtestosterone leads to increases in frailty or disability2 andworseninghand function8, nonehave reportedan increased riskof falls in patients receiving ADT. One small study9 suggestedthat use of ADT leads to significant functional and physicalimpairment, and patients are at a greater risk of falls than asimilar-aged cohort. This study was limited by a smallconvenience sample of 50 patients, short follow-up (3months),and lack of control subjects who were not taking ADT.

Table 1 – Baseline characteristics of participants acrosscohorts.

Variables ADTusers

PCcontrols

Healthycontrols

N 88 86 86Mean age, y (SD) 69.6 (6.7) 69.7 (6.7) 68 (7.2)Mean education, y (SD) 14.4 (4.3) 15.6 (4.0) 16 (3.5)Mean Gleason score (SD) 7.5 (1.1) 6.6 (0.8) NAStage T1C 25 40 NA

T2A 19 27 NAT2B 18 15 NAT2C 8 2 NAT3 18 2 NA

1.2. Falls and fall-induced injuries

Falls and fall-induced injuries among older people are a majorpublic health concern worldwide. Falls among the elderly carryhigh costs to individuals and society10, accounting for over 70%ofall injury-relatedadmissions tohospitals forpeopleover65 years.About one third of people over age 65 fall each year, and thefrequency ismarkedly increasedwith advancing age,with 50%ofolder adults falling annually after age 8011. Falls are also theleadingcauseofhip fracturesandplacement inanursinghome12,and the sixth leading cause of death in the older population13,14.

Since ADT use may be associated with declines in musclemass and strength and worse fatigue, these changes predisposeADT users to a greater risk of falls. ADT use also leads toaccelerated osteoporosis7,15, which may independently increasethe risk of falls16. Given the biologically plausible link betweenADTand increased fall risk, alongwith the limitedpublisheddata,this potentially clinically important issue requires clarification.We therefore conducted a study to prospectively compare thenumber of falls in men on ADT compared to controls. We alsoexamined other risk factors for falling in this older population.

Charlsonscore

0 62 (70%) 61 (71%) 53 (62%)1 13 (15%) 19 (22%) 23 (27%)2+ 13 (15%) 6 (7%) 10 (11%)

Current smokers 26 (29.5%) 39 (45%) 29 (34%)Regular alcohol use 37 (42%) 44 (51%) 37 (43%)Currently working 28 (32%) 29 (34%) 30 (35%)Married 61 (70%) 75 (87%) 56 (65%)Bone mineraldensity

AP lumbarspine mean (SD)

1.12 (0.26) 1.29 (1.39) NA

Femoral neckmean (SD)

0.87 (0.15) 0.82 (0.15) NA

Total hip mean(SD)

1.02 (0.15) 1.03 (0.12) NA

Previoustreatment

External beamradiotherapy

48 41 0

RP 12 26 1RP+RT 4 4 0

Note: ADT=Androgen Deprivation Therapy; PC=Prostate Cancer,RP=Radical Prostatectomy, RT=Radiotherapy.

2. Methods

This study is a secondary pre-specified analysis from aprospective cohort study. Three separate groups of men wereenrolled: prostate cancer patients commencing on ADT (ADTusers); patients with prostate cancer who were not taking ADT(PC controls); andhealthy controlswithoutprostate cancer.ADTusers and PC controls had biopsy-confirmed prostate cancerand no evidence ofmetastatic disease.Men in each cohort werefrequency-matched on age (3 strata), education (2 strata), andwalking independence at baseline (yes/no).

Patients were excluded if they had another activemalignan-cy, had a life expectancy of less than 1 year, were not fluent inreading/writing English, had a major neuropsychiatric abnor-mality, or were unable to ambulate without human assistance.

Participants were recruited from prostate cancer clinics(Urology and Radiation Oncology) across the PrincessMargaretHospital, a tertiary care academic cancer center. A few menwere recruited through advertisements placed in local news-papers as well as across the hospital. Healthy controls weremostly recruited from Urology/Men's Health Clinics as well asthrough hospital and local newspaper advertisements. Due totime constraints in clinic, we did not keep a recruitment log ofapproached patients.

2.1. Baseline assessment

We enrolled 260 patients at baseline. At baseline, along withcollecting socio-demographic, disease, comorbidity, and med-ication information, we asked all patients about any falls inthe past 12 months.

2.2. Functional measures

Physical performance measures and self-reported question-naireswere used to assess the functional status of patients. Thephysical performancemeasures consisted of the 6-minute walktest (6MWT), grip strength, and the Timed Up and Go task.

The 6MWT was originally used by physicians to assesspatients with chronic lung disease. The 6MWT is a submaximalexercise test that has been shown to be both feasible and reliablein older adults17, and correlateswellwith daily physical activities.

34 J O U R N A L O F G E R I A T R I C O N C O L O G Y 1 ( 2 0 1 0 ) 3 2 – 3 9

Grip strength is an independent predictor of mortality inolder adults and may identify patients, including those with ahigh level of function, who are at risk of deterioratinghealth18,19. Grip strength was measured in this study using aJamar dynamometer three times in each hand20.

Declines in lower extremity function are predictive ofsubsequent disability in older adults21. To assess lowerextremity function, we used the Timed Up and Go task,which evaluates balance and basic functional mobility22,23.

Self-reported ability to perform basic activities of dailyliving (ADL) was measured using the Barthel Index24 andinstrumental activities of daily living (IADL) using the Lawtonand Brody scale25.

2.3. Follow-up assessments

Every patient in each cohort was seen at 3 months, 6 months,and 12 months after their baseline visit. At each subsequentvisit, patients completed all three physical function tests(Timed Up and Go, 6MWT and grip strength) as well as self-reported tests for ADL and IADL. Patients were also askedspecifically if they had a fall or new balance problem since theprior visit.

Table 2 – Baseline characteristics of fallers and non-fallers.

Variables Characteristics

NCohort ADT users

PC controlsHealthy controls

Age (continuous) Per yearWorking status Working

Not workingMarital status Married

Not marriedLiving arrangement Alone

OtherEducation Per yearBone mineral density AP lumbar spine (mean)

Femoral neck (mean)Total hip mean

Smoking Non smokerSmoker

Alcohol DrinkerNon drinker

Charlson score 012+

Atrial fibrillationArthritisStrokeHearing impairmentVisual impairmentBarthel score (mean)Lawton–Brody score (mean)Timed Up and Go, s (mean)6-minute walk, feet distance (mean)Grip strength, kg (mean)

Note: ADT=Androgen Deprivation Therapy; PC=Prostate Cancer.a Chi-Square.b T-test.

2.4. Potential risk factors for falls

Basedonprevious literature,we identifiedanumberofpotentialrisk factors for falling inour cohort. The followingvariableswereconsidered: previous history of falls (dichotomous); age (mod-elled as either a continuous or categorical variable); workingstatus (working ornotworking, i.e. retired/social assistance/sickleave); marital status (married or other); specific comorbidities(stroke, arrhythmias, arthritis, vision impairment, hearingimpairment);CharlsonComorbidity score (categorical); smoking(ever/never); alcohol (regular user/non-user); education (contin-uous); ADL score (continuous); IADL score (continuous); andphysical performance measures (6MWT, grip strength, TimedUp and Go test) (all continuous).

2.5. Statistical analyses

Baseline characteristics for all patients were described usingmeans for continuous variables and frequencies for categor-ical variables. Comparing patients across cohorts and amongfallers and non-fallers at baseline (based on self-report) wasdone using ANOVA for continuous variables and chi-squaretests for categorical variables.

Fallers Non-fallers P-value

36 (13.8%) 224 (86.2%) n/a13 (14.7%) 75 (85.3%) 0.13a

7 (8.1%) 79 (91.9%)16 (18.6%) 70 (81.4%)

0.13b

4 (4.6%) 83 (95.4%) 0.002a

32 (18.7%) 139 (81.3%)20 (10.4%) 172 (89.6%) 0.006a

16 (23.9%) 51 (76.1%)13 (25%) 39 (75%) 0.010a

23 (11.1%) 184 (88.9%)0.064b

1.16 1.21 0.84b

0.86 0.85 0.68b

0.99 1.02 0.40b

9 (9.6%) 85 (90.4%) 0.13a

27 (16.5%) 137 (83.5%13 (16.8%) 105 (83.2%) 0.19a

23 (11.0%) 114 (89%)21 (11.9%) 155 (88.1%) 0.075a

7 (12.7%) 48 (87.3%)8 (27.6%) 21 (72.4%)3 (8.3%) 14 (6.2%) 0.64a

18 (50%) 71 (31.7%) 0.032a

4 (11%) 13 (5.8%) 0.23a

5 (13.9%) 23 (10.3%) 0.52a

3 (8.3%) 21 (9.3%) 0.84a

97.4 98.1 0.41b

15.6 15.6 0.98b

7.8 6.6 0.003b

1467.1 1587.1 0.020b

37.9 41.5 0.023b

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Based on their responses at the follow-up visits, patientswerecharacterized as having or not having at least one fall in the12months after baseline for analytic purposes. Similar analysesof predictors of falling were done as at baseline, examining riskfactors among fallers and non-fallers. The risk of having a fallwithin 1 year of study entry was analyzed using logisticregression. Univariate logistic regression was performed first;variables with a p-value <0.10 were included in themultivariablemodel. Age was forced into the multivariable model. Wespecifically examined for collinearity among variables using thevariance inflation factor, and removed the collinear variablewitha poorer model predictive ability. We then individually removedvariables fromthemultivariablemodelwitha p-value>0.05usinga backward stepwise approach. This strategy was adopted tostrike a balance between the risk of overfitting26 and the biases ofstepwise model selection27. We also examined risk factors for aprior fall among study participants at baseline, including theabove covariates (except for prior history of falls). We reportedresults for both the full multivariable model (minus collinearvariables) and the final multivariable model. Model calibrationand discrimination for multivariable logistic models wereassessed using the Hosmer–Lemeshow statistic and c-statistic,respectively. The study was approved by the Research EthicsBoard of the Princess Margaret Hospital.

Table 3 –Multivariable model showing predictors of fallsin year prior to ADT use.

Full multivariable model Reducedmultivariable model

Variable Odds ratio(95% CI)

P-value Odds ratio(95% CI)

P-value

Age, per year 0.98(0.91, 1.05)

0.50 1.00(0.94, 1.07)

0.86

Education 0.97(0.88, 1.07)

0.56

Charlson score 1.24(0.78, 1.96)

0.35

Grip strength(per kg)

0.97(0.92 ,1.03)

0.32

Timed Up and Go(per second)

1.24(1.04, 1.49)

0.019 1.29(1.09, 1.54)

0.003

Marital status(married vs other)

0.46(0.20, 1.04)

0.061 0.42(0.19, 0.93)

0.031

Working status(not working vsworking)

4.31(1.35, 13.73)

0.013 4.59(1.45, 14.51)

0.009

Arthritis 1.69(0.75, 3.81)

0.21

ADT users 0.64(0.25, 1.59)

0.33 0.68(0.28, 1.63)

0.39

PC controls 0.43(0.15, 1.22)

0.11 0.41(0.15, 1.16)

0.093

Healthy controls Referent Referent

Note: ADT=Androgen Deprivation Therapy; PC=Prostate Cancer.

3. Results

3.1. Baseline characteristics

Of 260 patients who were enrolled at baseline, 235 patientsreturned for their 3 month (76 ADT users, 80 PC controls, and 79Healthy controls) visit, 229 for their 6 month visit (76, 75, and 78,respectively), and 219 patients for their 12month follow-upvisit(72, 74, and 73, respectively). Altogether, 250 patients completedat least one follow-up assessment. Of the 10 patients who didnot return for any follow-up visits, 5 patientswithdrew from thestudy because of lack of time/interest, 2 patients died, 2 patientsdid not provide any reason, while 1 patient had a stroke withhemiparesis. No significant differences were noted in baselinecharacteristics or prior history of falls among the 10 patientswho did not complete any follow-up visit compared to ongoingstudy participants (data not shown).

Of the remaining 250 patients, the 3 cohortswere reasonablywell-matched at baseline with respect to age, educational level,comorbidity, and functional status. As expected, ADT users hadhigher-stage and worse-grade disease than PC controls. Table 1.

3.2. Risk of prior fall

At baseline, 36 (13.8%) patients reported one or more falls in theprevious 12months. Among the cohorts, 15% of ADT usersreportedat leastone fall compared to8%ofPCcontrolsand19%ofhealthy controls (p=0.132). In univariate analyses, not working,being unmarried, a greater Charlson score, and arthritis wereindependent predictors of a prior fall (Table 2). Self-reportedability to perform basic ADL and IADL were not found to besignificantly associatedwith prior falls, whereas 6MWTdistance,grip strength, and the Timed Up and Go task were found to besignificant independent predictors of prior fall risk (Table 2).

In the multivariable model, significant predictors of priorfalls included Timed Up and Go, marital status, and workingstatus, while there was no significant difference by cohort orwith increasing age (Table 3). Living arrangement and 6MWTwere removed because of collinearity with marital status andTimed Up and Go, respectively. Model discrimination wasgood, with a C-statistic of 0.777, as was model calibration(Hosmer–Lemeshow statistic p-value>0.05).

3.3. Fall risk over 12 months

Over 12 months of follow-up, 62 (25%) participants reportedone or more falls. The number of fallers differed amongcohorts — 35% of ADT users, 18% of PC controls, and 22% ofhealthy controls (p=0.035).

In univariate analyses, in addition to cohort, other inde-pendent predictors of falls included being unmarried (20% ofmarried versus 38% of single or divorced men reported a fall,p=0.005), prior falls reported at baseline (53% among priorfallers and 21% among non-fallers, p=<0.001), and workingstatus (18% among working and 28% among non-workingparticipants, p=0.078). Although ADL score was associatedwith falls (p=0.021), IADL score was not (p=0.177). All threephysical performance measures were also found to besignificant predictors of falls at 12 months (Table 4).

We used a similar approach as in Section 3.2 to examine fallsover 12months in amultivariable logistic model. Living arrange-ment was removed from the multivariable model because ofcollinearity with marital status. Similarly, Timed Up and Go and

Table 4 – Crude risk of falls over 12 months after study entry.

Variables Characteristics Fallers Non-fallers P-value

N 62 (24.8%) 188 (75.2%) n/aCohort ADT users 29 (34.5%) 55 (65.5%) 0.035a

PC controls 15 (18.1%) 68 (81.9%)Healthy controls 18 (21.7%) 65 (78.3%)

Age (continuous) Per Year 0.043b

Prior history of falls Falls at baseline 19 (56%) 15 (44%) <0.001a

Working status Working 15 (18%) 68 (82%) 0.078a

Not working 47 (28.3%) 119 (71.7%)Marital status Married 38 (20.3%) 149 (79.7%) 0.005a

Single 24 (38.1%) 39 (61.9%)Living arrangement Alone 21 (42%) 29 (58%) 0.002a

Other 41 (20.5%) 159 (79.5%)Education Per year 0.069b

Smoking Non smoker 20 (21.3%) 74 (78.7%) 0.30a

Smoker 42 (27.1%) 113 (72.9%)Alcohol Drinker 25 (22.1%) 88 (77.9%) 0.39a

Non drinker 36 (26.9%) 98 (73.1%)Charlson score 0 37 (21.5%) 135 (78.5%) 0.004a

1 11 (22%) 39 (78%)2+ 14 (50%) 14 (50%)

Atrial fibrillation 6 (9.6%) 9 (4.8%) 0.16a

Arthritis 32 (51.6%) 55 (29.2%) 0.001a

Stroke 5 (8.0%) 11 (5.8%) 0.54a

Hearing impairment 7 (11.3%) 20 (10.6%) 0.89a

Visual impairment 6 (9.6%) 18 (9.6%) 0.98a

Barthel score (mean) 97.4 98.4 0.018b

Lawton–Brody score (mean) 15.3 15.7 0.24b

Timed Up and Go, s (mean) 7.9 6.6 0.001b

6-minute walk, feet distance (mean) 1512.4 1693.4 <0.001 bGrip strength, kg (mean) 38.2 40.5 0.073b

Note: ADT=Androgen Deprivation Therapy; PC=Prostate Cancer.a Chi-Square.b T-test.

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grip strength were removed because of collinearity with the6MWT(Table5). Statistically significant independentpredictors inthe multivariable model included being unmarried, prior historyof falls, and arthritis. ADT use was associated with a trend

Table 5 –Multivariable model showing predictors of falls over 1

Full multivariable model

Variables Odds ratio 95% CI

Age, per year 1.02 (0.96, 1.08)Education 1.00 (0.92, 1.09)Charlson score 1.30 (0.87, 1.94)Marital status (married vs other) 0.43 (0.21, 0.90)Alcohol consumption 0.97 (0.49, 1.90)Working status 1.12 (0.52, 2.44)Arthritis 2.42 (1.20, 4.89)6-minute walk 0.92 (0.82, 1.04)Barthel score 0.92 (0.83, 1.02)Prior history of falls in last year 3.71 (1.61, 8.57)ADT users 1.77 (0.79, 3.93)PC controls 0.93 (0.38, 2.25)Healthy controls Referent

Note: ADT=androgen deprivation therapy; PC=prostate cancer.

towards an increased risk of falls (odds ratio 1.96, 95% confidenceinterval 0.91 to 4.19, p-value=0.083). Model discrimination wasgood, with a C-statistic of 0.765, and model fit was also good(Hosmer–Lemeshow statistic p-value>0.05).

2 months.

Reduced multivariable model

P-value Odds ratio (95% CI) P-value

0.50 1.03 (0.98, 1.08) 0.230.960.200.025 0.41 (0.21, 0.84) 0.0140.930.770.014 2.39 (1.23, 4.63) 0.0090.200.120.002 4.18 (1.88, 9.32) <0.0010.076 1.96 (0.91, 4.19) 0.0830.35 0.94 (0.40, 2.18) 0.88

Referent

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4. Discussion

In this prospective cohort study of men on ADT, we demon-strated that ADT may be associated with an increased risk offalls over 12 months compared to controls. Although wedemonstrated a trend towards an increased risk of falls withADT use, the 95% confidence interval overlapped unity, likelydue to the relatively small number of events (n=62).We recentlyreported that ADT usewas associatedwith attenuation in gainsin endurance and loss of grip strength (as a measure of upperextremity strength) over time, compared to PC controls andhealthy controls. Most of these losses were observed within 3–6 monthsofADT initiation, andpersisted for 12 months28. Thus,there are strong physiological grounds to hypothesize that ADTuse will increase fall risk, primarily through muscle atrophy,loss of strength, and fatigue. However, further follow-up of fallsin our cohort is planned, and larger studies may be needed toconfirm our findings.

Several previous studies have suggested that ADT use leadsto decreases in muscle mass29, function8, osteoporosis30,31, andincreases in frailty32, but very few have examined falls as anoutcome33. Only one prior study by Bylow et al. demonstratedthat older men with prostate cancer on ADT appear to have anincreased riskof falls9. That studywas limitedby short follow-upand absence of a control group. Thus it is difficult to concludewhether ADT alone was responsible for falls in those patients.

There are many probable causes of falls in older adults, andfalls are often due to multiple causes in an individualpatient34,35. In our study, an interesting finding was thatphysical performance tests, ADL scores, and IADL scores werenot independently predictive of future falls; rather, simple non-physical factors — a prior history of falls, arthritis, and beingunmarried — were important predictors of future falls. This islikely because of the strong relationship between physicalperformance, activities of daily living, and fall risk. A recentstudy suggested that marriage protects men from chronicinflammation36. Remainingmarriedmayalso reflect individualswho have less comorbidity, disability, have greater socialsupport and better socio-economic status,whichmay indirectlyprotect against falls. Why marital status was associated withlower fall risk in our study should be further studied.

We tried to overcome several of the limitations of priorwork by including relevant control groups, follow-up at regularintervals, and a larger sample size. But our study had its ownlimitations. We had only 62 patients reporting falls, limitingour power to detect an impact of ADT. We also did not collectinformation on patients' physical activity. This may beimportant because resistance exercise has been shown toameliorate the impact of ADT onmuscle strength, fatigue, andquality of life37,38. Also, as this study was a secondary pre-specified analysis from a larger prospective cohort study inwhich patients were matched on 3 variables, we could notmatch patients on a prior history of falls. Thus there is likelyresidual confounding, as suggested by differences in prior fallsacross the three cohorts at baseline. We attempted to adjustfor this in ourmultivariablemodels by including prior falls as acovariate. Our patients were also relatively healthy, asdemonstrated by their physical performance and ADL scoresat baseline. More frail men may be at greater risk of falls.

Finally, our study featured patients from one center, limitingits generalizability.

Our study has important clinical implications. Physicianstaking care of patients while they are onADT should specificallyscreen these patients for other fall risk factors, namely arthritisand a prior history of falls. Also, physicians should better screenpatients who are not married or living alone since one of thehypotheses of the relationship between falls and marital statusis that married people may have more social support at homewhichmaymitigate fall risk. Thosewith one ormore risk factorsfor falling beyond ADT, particularly one ormore prior falls, maybenefit from a more detailed assessment in a specialized fallsclinic39. Prostate cancer clinicians should also recognize thatfalls are a major risk factor for morbidity and mortality in theelderly population. Moreover, ADT use increases the risk offracture31,40. Thus, careful attention needs to be paid tooptimizing bone health41 and recommending physical activityand/or resistance training37,38 formen on ADT. Finally, for thoseclinicians and patients considering ADT for indications forwhich strong randomized trial evidence of survival benefitdoesnot exist (e.g. biochemical relapse), itmay be appropriate todefer or avoid ADT use in those men at higher risk of falls.

Conflict of interest

None of the authors have any financial conflicts of interest todeclare with respect to this manuscript.

Author contributions

Conception and Design - SH, SMHAData Collection - SH, HB, NHAnalysis and Interpretation - SH, HB, NH, SMHAManuscript Writing - SH, HB, NH, SMHA

Acknowledgements

Dr. Hussain was supported by the Toronto General andToronto Western Research Fund. This study was supportedby a grant from the Canadian Cancer Society. Dr. Alibhai is aResearch Scientist of the Canadian Cancer Society.

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Shabbir Hussain, MD is a medical graduate from Pakistan. Heis currently working as research assistant at Departments ofMedicine and Health Policy, Management, and Evaluation atthe University Health Network under the supervision ofDr. Shabbir Alibhai. He is also applying this year for an InternalMedicine residency position in the United States. His futuregoal is to complete his residency in Internal Medicine andpursue a fellowship in Oncology.

Shabbir Alibhai, MD, MSC is an Assistant Professor in theDepartments of Medicine and Health Policy, Management, andEvaluation at the University of Toronto. He is a staff physicianand researcher at the University Health Network and TorontoRehabilitation Institute, and a Research Scientist of the Cana-dian Cancer Society. His research interests are in geriatriconcology, particularly in understanding treatment-related toxi-cities and improving quality of life, fatigue, and function in olderpeople with prostate cancer and acute leukemia.