Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Overview of cancer incidence and mortality among people living with HIV/AIDS in British Columbia, Canada: Implications for HAART use and NADM development

  • Connie G. Chiu1,
  • Danielle Smith2, 3,
  • Kate A. Salters2, 3,
  • Wendy Zhang3,
  • Steve Kanters3,
  • David Milan3,
  • Julio S.G. Montaner3, 4,
  • Andy Coldman5,
  • Robert S. Hogg2, 3 and
  • Sam M. Wiseman1Email author
BMC Cancer201717:270

DOI: 10.1186/s12885-017-3229-1

Received: 8 March 2016

Accepted: 24 March 2017

Published: 14 April 2017

Abstract

Background

The objective of this study is to evaluate the incidence of non-AIDS defining malignancies (NADMs) among people living with HIV/AIDS (PLWHA) in British Columbia, focusing on clinical correlates, highly active antiretroviral therapy (HAART) use, and survival, in order to elucidate mechanisms for NADM development.

Methods

A retrospective population based analysis was carried out for individuals with HIV/AIDS that began their treatment between 1996 and 2008.

Results

There were 145 (2.95%) NADMs and 123 (2.50%) AIDS defining malignancies (ADMs) identified in 4918 PLWHA in the study population. NADMs were represented by a range of cancer types including, most commonly, lung cancer, followed by anal, breast, head/neck, prostate, liver, rectal, and renal cancers. PLWHA had a SIR of 2.05 (CI:1.73, 2.41) for the development of NADMs compared to individuals without an HIV/AIDS diagnosis in the general population. Independent factors significantly associated with a NADM were: male gender, older age, lower CD4 cell counts, previous NADM, absence of HAART (non-HAART versus HAART) and treatment during the early-HAART era (before 2000 versus after 2000).

Conclusions

NADMs represent an important source of morbidity for PLWHA. Use of HAART with its associated improvement in immune-restoration, and tailored targeted cancer screening interventions, may be beneficial and improve outcomes in this unique patient population.

Keywords

Cancer HIV Aids Epidemiology HAART Malignancy

Background

The advent of combination triple antiretroviral therapy (ART), later referred to as highly active ART (HAART), was found to result in superior patient outcomes and sustained HIV suppression [1, 2]. Reports of remarkable improvements in patient survival and morbidity with the expanded use of the HAART regimen soon followed, ushering in a new era in which HIV/AIDS became viewed as a chronic manageable disease [36]. The longevity experienced by people living with HIV/AIDS (PLWHA) in the modern HAART era has resulted in increasing vulnerability to age-related diseases and new health challenges [7, 8]. The decline in the incidence of AIDS defining malignancies (ADMs) (Kaposi’s sarcoma, non-Hodgkin lymphoma, and invasive cervical cancer) has been accompanied by a dramatic increase in the incidence of non-AIDS defining malignancies (NADMs) [911]. However, the incidence of NADMs amongst PLWHA does not appear to be attributable to age alone, as PLWHA have an increased risk of malignancy compared to age-matched cohorts in the general population. While behavioural differences between HIV-positive and HIV-negative populations must be noted, studies controlling for smoking status found PLWHA to remain at increased risk for lung cancer development when compared to the general population [12, 13]. Furthermore, as well as an increased risk of viral co-infection (such as Hepatitis viruses, Human Papillomaviruses, and the Epstein-Barr virus) [1418] and incidence of cancers attributable to these tumor-associated oncogenic viruses, PLWHA also have a higher incidence of cancer types that have no known viral etiology, notably lung cancer [19]. Finally, cancer-related outcomes may vary by HIV serostatus as NADM related mortality is observably higher compared to the general population [20]. Thus, fundamental characteristics reflective of the immune and health status of PLWHA represent important factors that may mediate the differential cancer risk observed in the HIV/AIDS population.

This is amongst the first Canadian studies reporting on NADMs in PLWHA. It also represents one of only a few contemporary reports evaluating cancer risk during the late-HAART era. Our study is uniquely poised because antiretroviral medications are centrally administered and are free of charge in British Columbia, Canada, resulting in a comprehensive population based database of all individuals receiving antiretroviral therapy in the province. Thus, our study captured detailed drug information and reduces confounding bias related to access to care. The objective of this study was to determine the incidence, clinical correlates, and survival outcomes of NADMs amongst PLWHA in British Columbia, Canada, during the HAART era.

Methods

Study design and data sources

This retrospective study utilized a linkage of health administrative data from two comprehensive population health databases in Bristish Columbia, Canada. The British Columbia Cancer Registry (BCCR) is a province-wide mandatory reporting database that records all new cancer diagnoses in British Columbia. The BCCR catalogues individual demographic, cancer specific and mortality data for all cancer patients in the province. The HIV/AIDS Drug Treatment Program (DTP) Registry was established by the British Columbia Centre for Excellence in HIV/AIDS (BC-CfE). All antiretroviral medications are distributed at no cost to all individuals with an HIV/AIDS diagnosis living in British Columbia through a centralized single-payer system and are recorded in the program registry. The registry was created to monitor trends and regional differences in access to antiretroviral therapy and to evaluate the success of treatment on reducing HIV-related morbidity and mortality in British Columbia. The DTP Registry contains individual administrative records of patient antiretroviral drug regimens as well as demographic, clinical, and laboratory data. The BCCR and the DTP Registry are expected to provide a comprehensive listing of all individuals with a cancer diagnosis and all individuals with an HIV/AIDS diagnosis undergoing antiretroviral therapy, respectively, in British Columbia. This study was approved by our institutional research ethics board.

Data linkage

A probabilistic-match procedure based on Personal Health Numbers (PHNs), names, and dates of birth contained in the BCCR and DTP registries was carried out to generate a province-wide listing of all individuals with an HIV/AIDS diagnosis that had or had not been diagnosed with cancer. This cohort was then enriched by the DTP database with antiretroviral related treatment information. All individual names and identifying information were removed from the resulting datasets before being provided to the study data analysts at the BC-CfE. Analyses were then carried out on the aggregate individual level anonymized dataset.

Study criteria

Individuals in the DTP registry were included in the study if their antiretroviral therapy was initiated between August 1st, 1996 and March 31st, 2008. The study start date was chosen to reflect the beginning of widespread use of HAART in British Columbia. Furthermore, the study also separates individuals into the early-HAART (1996–2000) and late-HAART (2000 and later) eras, distinguished by the introduction of a more effective HAART regimen in 2000. Patients were excluded if they were aged 18 years or younger at initiation of antiretroviral therapy. All cases of cutaneous squamous cell carcinoma and basal cell carcinoma were excluded due to suspected non-uniform reporting for these cancers as cases may be topically treated without pathologic confirmation or registry reporting. Follow-up time was until December 31st, 2008. Both NADMs and ADMs diagnosed after 1996, regardless of HAART status, were evaluated, as were predictors of NADM while receiving treatment. While a few individuals in the study cohort were diagnosed with multiple cancer types, only the first NADM and ADM that was diagnosed prior to, and after, the initiation of HAART therapy was entered into the study database.

Statistical analyses

To calculate the standardized incidence ratios (SIR), indirect method of adjustment for age and sex was used. We applied BC population (as our standard population via the BCCR) cancer rates to our study sample to determine expected counts, then we used ‘observed count/expected count’ to determine the standardized incidence rate (SIR). Yearly population incidence rates were available from 1996 to 2003 and for 2007. Expected cases for 2004 and 2005 were based upon incidence rates for 2003, and expected cases for 2006 through 2008 were obtained from the 2007 incidence rates.

The study cohort was used to evaluate the determinants of NADM incidence. The variables evaluated in these analyses included: gender, age at enrollment in DTP, nadir CD4 level, baseline viral load, history of intravenous drug use, presence of ADM, presence of Hepatitis C infection, use of HAART (non-HAART versus HAART), and HAART era at start of antiretroviral therapy (early-HAART versus late-HAART, i.e. prior to 2000 versus 2000 and later). HAART was defined as use of combination triple-antiretroviral therapy, and non-HAART was defined as use of mono- or dual-antiretroviral therapy. Contingency tables were constructed utilizing Fisher’s exact test for evaluation of association between variables and cancer incidence. Logistic regression was then utilized to determine the variables that were independent of the development of NADMs. As these were explanatory models, the model selection was performed by minimizing the Akaike information criterion (AIC) while limiting the type III p-values to less than 0.20.

Kaplan-Meier product limit estimates of cumulative overall survival were obtained for NADM cases in the study cohort. Patients contributed to time at risk (in person-years) from start of therapy to either date of NADM diagnosis or date of censoring. Patients were censored because they had: no NADM by the end of the study period, moved out of province, or were lost to follow-up. All individuals in the DTP cohort, including those individuals diagnosed with an ADM, contributed to the person-time calculation.

Results

The demographic and clinical characteristics of HIV/AIDS patients in the study population are summarized in Table 1. The cohort consisted of 4918 men and women. The median follow-up time was 64 months (Interquartile range (IQR): 32 to 112 months). Study participants were more likely to be men, younger than 50 years, and have a nadir CD4 level lower than 200 cells/mm3. The majority of the study HIV/AIDS population did not have an ADM at the start of the study period upon initiation of antiretroviral therapy. All patients in the study cohort received antiretroviral drug therapy, with the majority of these individuals receiving HAART (combination triple-therapy), and only a few patients receiving non-HAART therapy (mono- or dual-antiretroviral therapy).
Table 1

Clinical characteristics of PLWHA in the study population (n = 4918)

Clinical characteristic

Number (Percent) of Individuals

Gender

 

 Male

4016 (81.7%)

 Female

902 (18.3%)

Age (years) at Start of Anti-retroviral Therapy

 

 Under 30

697 (14.1%)

 30–39

1932 (39.3%)

 40–49

1519 (30.9%)

 50 or more

770 (15.7%)

Nadir CD4 Level

 

 Less than 50

1402 (28.5%)

 50–99

686 (13.9%)

 100–199

1430 (29.1%)

 200 or more

1400 (28.5%)

Baseline Viral Load

 

(Log base 10)a

4.95 (4.40–5.00)

Intravenous Drug Use

 

 Yes

1766 (35.9%)

  No

3152 (64.1%)

ADM Status

 

 Yes

251 (5.1%)

 No

4667 (94.9%)

Hepatitis C Status

 

 Positive

2014 (41.0%)

 Negative

2110 (42.9%)

 Unknown

794 (16.1%)

Use of HAARTb

 

 Yes

4275 (86.9%)

 No

643 (13.1%)

Start of Antiretroviral Therapyc

 

 Early-HAART era (before 2000)

2093 (42.6%)

 Late-HAART era (2000 and after)

2825 (57.4%)

aMedian and Interquartile Range (IQR)

bAll individuals were treated with antiretroviral therapy (monotherapy, dual therapy or triple therapy); selected individuals were treated with HAART (triple therapy) according to guidelines at time of treatment

cThe year cut-point was utilized to represent use of more efficient HAART starting in the year 2000

Incidence of non-AIDS defining malignancies in study HIV/AIDS population

During the study period, 145 cases (2.95%) of NADMs and 123 cases (2.50%) of ADMs were diagnosed in 4918 PLWHA. These cases represent individuals that were all receiving antiretroviral therapy at the time of their cancer diagnosis. The NADMs there were diagnosed represented a range of cancer types and included cancers of the head and neck, breast, lung, gastrointestinal tract, genitourinary system and skin (Table 2). Of the NADMs diagnosed during the study period, the most common cancer sites were lung (20.7%) and anus (20.0%), followed by head and neck, liver, rectum, prostate, kidney and lymphatic system (>5% each). However, lung and anal cancers combined represented less than half of all NADMs, and PLWHA were at increased risk for a variety of other NADM types.
Table 2

NADMs identified in PLWHA receiving antiretroviral therapy by cancer type (n = 145)

Cancer type

Number of cases (% of NADMs)

Incidence rate (per 100,000 person-years)

Breast

5 (3.4)

100.03

Lung

30 (20.7)

104.97

Gastrointestinal

 Liver

8 (5.5)

27.99

 Gastric

2 (1.4)

6.99

 Colon

3 (2.1)

10.50

 Rectum

8 (5.5)

27.99

 Anal

29 (20.0)

101.47

Genital

 Vulva

3 (2.1)

60.02

 Testicle, scrotum

3 (2.1)

12.72

 Prostate

9 (6.2)

38.17

Urinary

 Bladder

2 (1.4)

6.99

 Kidney

8 (5.5)

27.99

Skin

 Melanoma

2 (1.4)

6.99

Other

 Unknown primary

5 (3.4)

17.50

 Soft tissue

2 (1.4)

6.99

 Brain, spinal cord

2 (1.4)

6.99

 Hematologic

5 (3.4)

17.50

 Lymphatic system

10 (6.9)

34.99

Total: 145 cases, 28,579.05 person-years

Female: 4998.45 person-years

Male: 23,580.60 person-years

The incidence of NADMs in our PLWHA study cohort was compared to their expected incidence in the general population (Table 3). Individuals with an HIV/AIDS diagnosis had a SIR of 2.05 (95% confidence interval [CI]: 1.73 to 2.41) for the development of NADMs compared to individuals not diagnosed with HIV/AIDS in the general population. A particularly large effect size was observed in younger men with HIV/AIDS (age 20 to 39), who had a SIR of 5.42 (CI: 3.31 to 8.38) for NADMs. A sub-group SIR analysis was carried out for the most frequently diagnosed NADM cancer types (Table 3). Cancers of the lung and anal canal had a significantly higher incidence in PLWHA compared to the general population.
Table 3

Standardized incidence ratio of NADMs in PLWHA on antiretroviral therapy

Age/Sex group

Number of NADM

Standardized Incidence ratios (95% CI)

Actual

Expecteda

All NADMs

 20–39/Male

20

3.69

5.42 (3.31,8.38)

 20–39/Female

3

1.88

1.60 (0.33, 4.66)

 40–59/Male

80

37.58

2.13 (1.69,2.65)

 40–59/Female

11

6.92

1.59 (0.79, 2.85)

 60–79/Male

29

19.40

1.49 (1.00,2.15)

 60–79/Female

2

1.31

1.53 (0.18, 5.52)

 Total

145

70.78

2.05 (1.73, 2.41)

Lung Cancer

 20–39/Male

1

0.06

16.55 (0.42, 92.21)

 20–39/Female

0

0.03

0 (0, 118.43)

 40–59/Male

14

4.16

3.37 (1.84, 5.65)

 40–59/Female

4

0.63

6.37 (1.74, 16.31)

 60–79/Male

11

2.90

3.80 (1.90, 6.79)

 60–79/Female

0

0.24

0 (0, 15.55)

 Total

30

8.02

3.74 (2.52, 5.34)

Anal Cancer

 20–39/Male

5

0.08

64.55 (20.98, 150.66)

 20–39/Female

0

0.005

0 (0, 749.71)

 40–59/Male

21

2.50

8.39 (5.19, 12.82)

 40–59/Female

1

0.26

3.82 (0.10, 21.29)

 60–79/Male

2

0.99

2.02 (0.24, 7.30)

 60–79/Female

0

0.05

0 (0, 69.03)

 Total

29

3.89

7.46 (4.99, 10.70)

aExpected number of NADMs are based on population incidence for that NADM

Clinical characteristics associated with a NADM in individuals with HIV/AIDS

Amongst PLWHA receiving antiretroviral therapy, there were significant differences in the demographic and clinical characteristics of individuals diagnosed with an NADM when compared to individuals not diagnosed with NADM (Table 4). To further evaluate this effect size, univariate analysis identified six variables significantly associated with the development of a NADM amongst PLWHA receiving antiretroviral therapy: male gender, older age at start of antiretroviral therapy, lower nadir CD4 cell counts, presence of another NADM prior to the initiation of antiretroviral therapy, absence of HAART, and start of antiretroviral therapy in the early-HAART era (i.e. prior to 2000) (Table 5). In multivariate modeling, the use of HAART (i.e. triple antiretroviral therapy) was protective against development of a NADM compared to mono−/dual- antiretroviral drug therapy (aOR: 0.64, CI: 0.43 to 0.95). A higher nadir CD4 count was also found to be an independent protective factor for the development of a NADM (aOR: 0.61, CI: 0.41 to 0.93 for a CD4 of 200 cells/mm3 or greater). Being over the age of 50 (aOR: 4.03, CI: 3.05–6.06) and having history of NADM before initiating ART (aOR: 3.42, CI: 1.50–7.83) were both associated with the development of NADM among the sample of PLWHA in our study.
Table 4

Clinical characteristics of PLWHA on antiretroviral therapy by NADM status

Clinical characteristic

Individuals with NADM

Individuals without NADMa

p-value

(N = 145)

(N = 4773)

Gender

 Male

129 (88.97%)

3887 (81.44%)

0.021*

 Female

16 (11.03%)

886 (18.56%)

Age (years) at Start of Antiretroviral Therapy

 Under 30

8 (11.8%)

689 (14.44%)

<0.001*

 30–39

41 (27.7%)

1891 (39.62%)

 40–49

41 (28.7%)

1478 (30.97%)

 50 or more

55 (31.8%)

715 (14.98%)

History of Intravenous Drug Use

 Yes

42 (28.97%)

1724 (36.12%)

0.077

 No

103 (71.03%)

3049 (63.88%)

Nadir CD4 (cells/mm3)

 200 or more

28 (19.31%)

1372 (28.75%)

0.040*

 100–199

48 (33.10%)

1382 (28.95%)

 50–99

28 (19.31%)

658 (13.79%)

 less than 50

41 (28.28%)

1361 (28.51%)

DM Status

 Yes

7 (4.83%)

244 (5.11%)

0.878

 No

138 (95.17%)

4529 (94.89%)

Hepatitis C Status

 Positive

52 (35.86%)

1962 (41.11%)

0.085

 Negative

75 (51.72%)

2035 (42.64%)

 Unknown

18 (12.41%)

776 (16.26%)

NADM Prior to Start of Antiretroviral Therapyb

 Yes

6 (4.14%)

54 (1.13%)

0.008*

 No

139 (95.86%)

4719 (98.87%)

Use of HAARTc

 Yes

112 (77.24%)

4163 (87.22%)

<0.001*

 No

33 (22.76%)

610 (12.78%)

Start of Antiretroviral Therapyd

 Early-HAART era (before 2000)

91 (62.76%)

2002 (41.94%)

<0.001*

 Late-HAART era (2000 and after)

54 (37.24%)

2771 (58.06%)

aIndividuals with no NADM were represented by patients with either no cancer diagnosis (no ADM or NADM) or with an ADM only (but no NADM)

bComparison groups were defined by individuals with diagnosis of NADM after initiation of antiretroviral therapy. There were 6 patients in the group “Individuals with NADM” that had a NADM prior to start of antiretroviral therapy and developed a second NADM during antiretroviral therapy. There were 54 patients in the group “Individuals without NADM” that had a NADM prior to antiretroviral treatment and did not develop an NADM during antiretroviral therapy

cAll individuals were treated with antiretroviral therapy (monotherapy, dual therapy, or triple therapy); selected individuals were treated with HAART (triple therapy) according to guidelines at time of treatment

dThe year cut-point was utilized to represent use of more efficient HAART starting in the year 2000

bolding and * indicates statistical significance at alpha 0.05

Table 5

Association of clinical characteristics with development of NADM in PLWHA receiving antiretroviral therapya (n = 4918)

Clinical characteristic

Unadjusted Odds ratio

Adjusted Odds ratiob

(95% Confidence Intervals)

(95% Confidence Intervals)

Gender

 Male

1.00 (−-)

---

 Female

0.59 (0.35–0.98)

Age (years) at Start of Antiretroviral therapy

 Under 50

1.00 (−-)

1.00 (--)

 50 or more

4.32 (3.08–6.06)

4.03 (3.05–6.06)

Nadir CD4 (cells/mm3)

 Less than 200

1.00 (−-)

1.00 (--)

 200 or more

0.63 (0.42–0.95)

0.61 (0.41–0.93)

NADM Prior to Start of Antiretroviral Therapyc

 No

1.00 (−-)

1.00 (--)

 Yes

4.87 (2.15–11.02)

3.42 (1.50–7.83)

Use of HAARTd

 No

1.00 (−-)

1.00 (--)

 Yes

0.76 (0.51–1.13)

0.64 (0.43–0.95)

Start of Antiretroviral Therapye

 Early-HAART era (before 2000)

1.00 (−-)

---

 Late-HAART era (2000 and after)

0.93 (0.31–1.34)

aAmongst individuals with a NADM diagnosis compared to individuals without a NADM (represented by patients with either no cancer diagnosis [no ADM or NADM] or with an ADM only [but no NADM])

bAdjusted odds ratio includes all variables listed under ‘Clinical Characteristic’ column. C-statistic = 0.689; multi-collinearity was verified and all variance inflation factors were less than 2

cOnly individuals with diagnosis of NADM after initiation of antiretroviral therapy were included in the comparison groups. There were 6 patients in the group “Individuals with NADM” that had a NADM prior to antiretroviral treatment and developed a second NADM during anti-retroviral therapy

dAll individuals were treated with antiretroviral therapy (monotherapy, dual therapy, or triple therapy); selected individuals were treated with HAART (triple therapy) according to guidelines at time of treatment

eThe year cut-point was utilized to represent use of more efficient HAART starting in the year 2000

Survival of PLWHA diagnosed with a NADM

Kaplan-Meier product limit estimates of cumulative overall survival were constructed for PLWHA in the study cohort (Fig. 1). Five patients were diagnosed with both a NADM and an ADM during the study period (i.e. during antiretroviral therapy) and were excluded from the categorical survival analysis. There was no significant difference in survival when comparing individuals diagnosed with an NADM compared to individuals diagnosed with an ADM prior to their cancer diagnosis (p = 0·073). Although a trend for improved early survival was observed in PLWHA diagnosed with an NADM compared to patients with an ADM, the survival probability of these two groups normalized at longer term follow-up. Amongst PLWHA receiving antiretroviral therapy, individuals with a NADM had a significantly lower survival compared to individuals without a cancer diagnosis (p < 0.001).
Fig. 1

Overall survival of PLWHA receiving anti-retroviral therapy by cancer status from time of a cancer diagnosis and b start of antiretroviral therapy

Discussion

This is amongst the first study to report on NADM incidence in a Canadian PLWHA population. The study specifically focused on PLWHA that were receiving treatment during the current HAART era. Outcomes were based on linked, single-payer administrative data from the Bristish Columbia Cancer Registry (BCCR) and the Drug Treatment Program (DTP), which provides a comprehensive analysis of province-wide antiretroviral use and cancer incidence in British Columbia, Canada.

Within our study, 2.95% (145 of 4918) of patients developed a NADM, which represents a significantly higher risk when compared to individuals without HIV/AIDS in the general population (SIR 2.05, CI: 1.73 to 2.41). The types of NADMs most commonly diagnosed in our study population were generally consistent with other reports of HIV/AIDS populations [2124]. The increased incidence of lung cancer that we observed in our study population has also been reported by other groups in PLWHA during both the pre-HAART and post-HAART eras [2528]. Our study also found a significantly increased incidence of anal cancer in PLWHA when compared to the general population, particularly for males aged 20 to 39 years (SIR 64.55, C.I. 20.98 to 150.66) and aged 40 to 59 years (SIR 8.39, C.I. 5.19 to 12.82). This is a higher incidence than observations made by other groups in which the SIR for development of anal cancer ranged from 6.8 to 10.3 [29, 30]. An increase in lung and anal cancer incidence is known to be associated with shared risk factors, such as increased incidence of smoking in PLWHA [27, 31].

Along with the increased incidence in lung and anal cancers, we also observed that the majority of NADMs were represented by other cancer types, including cancers of the head and neck, liver, rectum, prostate, kidney and lymphatic system. These observations have important implications on screening and treatment protocols for PLWHA. Screening interventions for a variety of cancer types have been proven to be beneficial in the general population, and studies have been encouraging for adoption of specific cancer screening practices for PLWHA [28]. The increased incidence of other cancer types, not just lung and anal cancers, suggests that physician awareness and cancer screening are especially important for PLWHA.

To further address the observed increase in NADMs diagnosed in PLWHA, our study analyzed the association between NADM development, HAART utilization, and host clinical characteristics. Previous studies have hypothesized that HAART utilization is indirectly associated with decreased cancer incidence due to improvement of host immune surveillance and clearance of tumor cells [32]. HAART utilization is also associated with increased survival, which results in a more prolonged time interval for the development of NADMs. Furthermore, in recent years, cancer incidence may also be influenced by intensified screening practices and greater physician awareness of the HIV/AIDS population.

Our current study found that individuals undergoing treatment in the late-HAART era (2000 and later) did not have a significantly decreased incidence of NADM when compared to individuals that began therapy during the early-HAART era (prior to 2000). However, this may be due to the fact that many individuals would have changed treatment regimens during the later HAART era and as such, cannot be simply categorized by the date of initiation. However our work does suggest that although NADM incidence is increased when compared with the general population, the use of more effective and efficient HAART therapy is protective against the development of NADMs in PLWHA through immune reconstitution, and this is also supported by previous research [3337]. This observation underscores the importance of early initiation of effective antiretroviral treatment, and implies that NADM incidence may be associated with immunological correlates in the HIV/AIDS population.

To further understand the mechanism by which HAART protects against NADM development, our present study found that a nadir CD4 level > 200 cells/mm3 was also protective against NADM development. Previous research has suggested that a higher percentage time with undetectable HIV RNA was protective against the development of NADMs, highlighting the importance of the host immune system in HIV clearance and NADM development [38]. Therefore, our observed association between CD4 levels and NADM development further supports the concept that HAART utilization may be protective due to its immune-restorative properties. These findings support early initiation of effective HAART therapy in order to maintain high CD4 levels. Furthermore, although the mechanisms that underlie the effects of HAART on the development of NADM in PLWHA are currently poorly understood, our observations suggest the importance of host immunological factors.

Previous studies have also suggested an association between HAART utilization and NADM incidence. In a study by Burgi et al. reporting on a cohort of 4144 HIV-positive individuals treated at military clinics in the United States between 1988 and 2003, the use of HAART was significantly associated with lower rates of NADMs [39]. Furthermore, studies from Australia and Europe have also reported higher CD4 levels and HAART utilization as being protective against NADM development [40, 41]. These reports are consistent with our observation and further suggest that the on-going immune-restorative effects of HAART may be beneficial in reducing the risk of NADM in PLWHA.

In our current study, we also observed that the development of a NADM not only resulted in a significantly reduced survival in PLWHA when compared to PLWHA without a cancer diagnosis, but also a post-cancer survival probability similar to individuals diagnosed with ADMs. The similarity in these survival outcomes suggests similarities in host reactions to all types of malignancies, which could be due to the specific immune factors required to clear the cancer cells. This would suggest that regardless of whether a cancer diagnosed in PLWHA is an ADM or NADM, protection against its development is impacted by adequate immune function, and therefore importantly mediated by HAART therapy.

The current study had several limitations, many of which are a consequence of its retrospective design. Evaluation of the number of NADMs and ADMs is highly dependent upon the accurate reporting of cancer in the provincial database. Furthermore, attempts to evaluate the impact of HAART on NADM diagnosis, represented by the absence or presence of HAART as well as the start date of antiretroviral treatment, are also potentially confounded by the changes that occurred in treatments over time. Moreover, there is considerable heterogeneity across NADM, and over time, and it can be difficult to infer direct clinical benefits of HAART uptake from epidemiological trends, although we suggest that overall we see a positive association between higher CD4 cell counts and cancer incidence. Conversely, there are notable differences between individuals receiving HAART therapy compared to individuals receiving mono−/dual- antiretroviral treatment, as we have controlled for duration of HIV infection but are unable to control for varying effects of therapeutic changes over time. Furthermore, age and CD4 level were included in the multivariate modeling as an objective measure of the health status of the study population.

Conclusions

The current study provides a contemporary overview of cancer risk in a large population of PLWHA during the HAART era. Currently, NADMs are an important cause of morbidity in PLWHA. Utilization of HAART and its associated improved immune-restoration may be beneficial for these individuals. Unquestionably, the development of more effective cancer screening and prevention practices, that are not limited to anal and lung cancers, will be important in the future. Further study of cancer epidemiology in PLWHA is important and will lead to the development of strategies that improve outcomes for this unique population.

Abbreviations

ADM: 

AIDS-defining malignancy

AIC: 

Akaike information criterion

ART: 

Antiretroviral Therapy

BC-CfE: 

British Columbia Centre for Excellence in HIV/AIDS

BCCR: 

British Columbia Cancer Registry

DTP: 

HIV/AIDS Drug Treatment Program

HAART: 

Highly active antiretroviral therapy

NADM: 

non-AIDS defining malignancy

PHN: 

Personal Health Number

PLWHA: 

People living with HIV/AIDS

SIR: 

Standardized incidence ratios

Declarations

Funding

This research study has not received any funding support from any source.

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article.

Authors’ contributions

CG carried out the literature search, drafted the figures, designed the study, collected data, carried out the data analysis, interpreted data, drafted the manuscript, and was involved in the critical review and edit of the manuscript. DS carried out the literature search, interpreted data, and was involved in the critical review and edit of the manuscript. SK drafted the figures, analyzed data, interpreted data, and was involved in the critical review and edit of the manuscript. DM drafted the figures, analyzed data, interpreted data, and was involved in the critical review and edit of the manuscript. WZ drafted the figures, analyzed data, interpreted data, and was involved in the critical review and edit of the manuscript. KS assisted with the data analysis, revisions and critical re-writes of the manuscript. JM collected data, interpreted data, and was involved in the critical review and edit of the manuscript. AC collected data, analyzed data, and was involved in the critical review and edit of the manuscript. RH designed the study, collected data, analyzed data, interpreted data, and was involved in the critical review and edit of the manuscript. SW carried out the literature search, drafted the figures, designed the study, carried out the data analysis, interpreted data, drafted the manuscript, and was involved in the critical review and edit of the manuscript. All authors read and approved the final manuscript.

Competing interests

No funding was received for this research study and there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Consent to publication

As no details/images/videos that would allow for identification of study participants are presented in this work Consent for Publication is not applicable.

Ethics approval and consent to participate

This study was approved and consent to participate was obtained by the ethics committee of Providence Health Care Research Ethics Board of St. Paul’s Hospital and University of British Columbia. The reference number is H08–01389. Informed consent was obtained from all the participants.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Surgery, St. Paul’s Hospital, & University of British Columbia
(2)
Faculty оf Health Sciences, Simon Fraser University
(3)
British Columbia Centre For Excellence In HIV/AIDS, Providence Health Care, St. Paul’s Hospital
(4)
Faculty of Medicine, University of British Columbia
(5)
Population and Preventive Oncology, British Columbia Cancer Agency

References

  1. Montaner JS, Reiss P, Cooper D, Vella S, Harris M, Conway B, Wainberg MA, Smith D, Robinson P, Hall D. A randomized, double-blind trial comparing combinations of nevirapine, didanosine, and zidovudine for HIV-infected patients: the INCAS trial. JAMA. 1998;279(12):930–7.View ArticlePubMedGoogle Scholar
  2. Hogg R, Yip B, Chan KJ, et al. Rates of disease progression by baseline CD4 cell count and viral load after initiating triple-drug therapy. JAMA. 2001;286(20):9.View ArticleGoogle Scholar
  3. Hogg R, Heath KV, Yip B, et al. Improved survival among HIV-infected individuals following initiation of antiretroviral therapy. JAMA. 1998;279(6):5.View ArticleGoogle Scholar
  4. Palella Jr FJ, Delaney KM, Moorman AC, Loveless MO, Fuhrer J, Satten GA, Aschman DJ, Holmberg SD. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV outpatient study investigators. N Engl J Med. 1998;338(13):853–60.View ArticlePubMedGoogle Scholar
  5. Gulick RM, Mellors JW, Havlir D, Eron JJ, Gonzalez C, McMahon D, Richman DD, Valentine FT, Jonas L, Meibohm A. Treatment with indinavir, zidovudine, and lamivudine in adults with human immunodeficiency virus infection and prior antiretroviral therapy. N Engl J Med. 1997;337(11):734–9.View ArticlePubMedGoogle Scholar
  6. Hammer SM, Squires KE, Hughes MD, Grimes JM, Demeter LM, Currier JS, Eron Jr JJ, Feinberg JE, Balfour Jr HH, Deyton LR. A controlled trial of two nucleoside analogues plus indinavir in persons with human immunodeficiency virus infection and CD4 cell counts of 200 per cubic millimeter or less. N Engl J Med. 1997;337(11):725–33.View ArticlePubMedGoogle Scholar
  7. Justice AC. HIV and aging: time for a new paradigm. Curr HIV/AIDS Rep. 2010;7(2):69–76.View ArticlePubMedGoogle Scholar
  8. Deeks SG. HIV infection, inflammation, immunosenescence, and aging. Annu Rev. Med. 2011;62:141–55.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Grulich AE, Li Y, McDonald AM, Correll PK, Law MG, Kaldor JM. Decreasing rates of Kaposi’s sarcoma and non-Hodgkin’s lymphoma in the era of potent combination anti-retroviral therapy. AIDS. 2001;15(5):629–33.View ArticlePubMedGoogle Scholar
  10. Cutrell J, Bedimo R. Non-AIDS-defining cancers among HIV-infected patients. Curr HIV/AIDS Rep. 2013;10(3):207–16.View ArticlePubMedGoogle Scholar
  11. Nguyen ML, Farrell KJ, Gunthel CJ. Non-AIDS-defining malignancies in patients with HIV in the HAART era. Curr Infect Dis Rep. 2010;12(1):46–55.View ArticlePubMedGoogle Scholar
  12. Engels EA, Pfeiffer RM, Goedert JJ, Virgo P, McNeel TS, Scoppa SM, Biggar RJ. Trends in cancer risk among people with AIDS in the United States 1980–2002. AIDS. 2006;20(12):1645–54.View ArticlePubMedGoogle Scholar
  13. Kirk GD, Merlo C, O’ Driscoll P, Mehta SH, Galai N, Vlahov D, Samet J, Engels EA. HIV infection is associated with an increased risk for lung cancer, independent of smoking. Clin Infect Dis. 2007;45(1):103–10.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Weiss RA. Viruses, cancer and AIDS. FEMS Immunol Med Microbiol. 1999;26(3–4):227–32.View ArticlePubMedGoogle Scholar
  15. Thio CL, Seaberg EC, Skolasky R, Phair J, Visscher B, Muñoz A, Thomas DL. HIV-1, hepatitis B virus, and risk of liver-related mortality in the multicenter cohort study (MACS). Lancet. 2002;360(9349):1921–6.View ArticlePubMedGoogle Scholar
  16. Salters KA, Cescon A, Zhang W, Ogilvie G, Murray MCM, Coldman A, Money D. Cancer incidence among HIV-positive women in British Columbia, Canada: Heightened risk of virus-related malignancies. HIV Med. 2016;17(3)188-95.
  17. Uccini S, Monardo F, Stoppacciaro A, Gradilone A, Aglianò AM, Faggioni A, Manzari V, Vago L, Cosianzi G, Ruco LP. High frequency of Epstein-Barr virus genome detection in Hodgkin’s disease of HIV-positive patients. Int J Cancer. 1990;46(4):581–5.View ArticlePubMedGoogle Scholar
  18. Silverberg MJ, Chao C, Leyden WA, Xu L, Tang B, Horberg MA, Klein D, Quesenberry CPJ, Towner WJ, Abrams DI. HIV infection and the risk of cancers with and without a known infectious cause. AIDS. 2009;23(17):2337–45. doi:10.1097/QAD.2330b2013e3283319184.View ArticlePubMedPubMed CentralGoogle Scholar
  19. Burke M, Furman A, Hoffman M, Marmor S, Blum A, Yust I. Lung cancer in patients with HIV infection: is it AIDS-related? HIV Med. 2004;5(2):110–4.View ArticlePubMedGoogle Scholar
  20. Marcus JL, Chao C, Leyden WA, Xu L, Yu J, Horberg MA, Klein D, Towner WJ, Quesenberry Jr CP, Abrams DI, et al. Survival among HIV-infected and HIV-uninfected individuals with common non-AIDS-defining cancers. Cancer Epidemiol Biomark Prev. 2015;24(8):1167–73.View ArticleGoogle Scholar
  21. Shiels MS, Cole SR, Kirk GD, Poole C. A meta-analysis of the incidence of non-AIDS cancers in HIV-infected individuals. J Acquir Immune Defic Syndr. 2009;52(5):611.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Castel AD, Young H, Akiwumi AM, Vargas A, Rogers K, West T, Levine PH. Trends in cancer diagnoses and survival among persons with AIDS in a high HIV prevalence urban area. AIDS Care. 2015;27(7):860–9.View ArticlePubMedGoogle Scholar
  23. Chaturvedi AK, Pfeiffer RM, Chang L, Goedert JJ, Biggar RJ, Engels EA. Elevated risk of lung cancer among people with AIDS. AIDS. 2007;21(2):207–13.View ArticlePubMedGoogle Scholar
  24. Zanet E, Berretta M, Martellotta F, Cacopardo B, Fisichella R, Tavio M, Berretta S, Tirelli U. Anal cancer: focus on HIV-positive patients in the HAART-era. Curr HIV Res. 2011;9(2):70–81.View ArticlePubMedGoogle Scholar
  25. Cadranel J, Garfield D, Lavole A, Wislez M, Milleron B, Mayaud C. Lung cancer in HIV infected patients: facts, questions and challenges. Thorax. 2006;61(11):1000–8.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Herida M, Mary-Krause M, Kaphan R, Cadranel J, Poizot-Martin I, Rabaud C, Plaisance N, Tissot-Dupont H, Boue F, Lang J-M. Incidence of non–AIDS-defining cancers before and during the highly active antiretroviral therapy era in a cohort of human immunodeficiency virus–infected patients. J Clin Oncol. 2003;21(18):3447–53.View ArticlePubMedGoogle Scholar
  27. Clifford GM, Polesel J, Rickenbach M, Dal Maso L, Keiser O, Kofler A, Rapiti E, Levi F, Jundt G, Fisch T. Cancer risk in the Swiss HIV cohort study: associations with immunodeficiency, smoking, and highly active antiretroviral therapy. J Natl Cancer Inst. 2005;97(6):425–32.View ArticlePubMedGoogle Scholar
  28. Sigel K, Wisnivesky J, Gordon K, Dubrow R, Justice A, Brown ST, Goulet J, Butt AA, Crystal S, Rimland D. HIV as an independent risk factor for incident lung cancer. AIDS (London, England). 2012;26(8):1017.View ArticleGoogle Scholar
  29. Frisch M, Biggar RJ, Goedert JJ, Group ACMRS. Human papillomavirus-associated cancers in patients with human immunodeficiency virus infection and acquired immunodeficiency syndrome. J Natl Cancer Inst. 2000;92(18):1500–10.View ArticlePubMedGoogle Scholar
  30. Dhir AA, Sawant S, Dikshit RP, Parikh P, Srivastava S, Badwe R, Rajadhyaksha S, Dinshaw K. Spectrum of HIV/AIDS related cancers in India. Cancer Causes Control. 2008;19(2):147–53.View ArticlePubMedGoogle Scholar
  31. Levine AM, Seaberg EC, Hessol NA, Preston-Martin S, Silver S, Cohen MH, Anastos K, Minkoff H, Orenstein J, Dominguez G, et al. HIV as a risk factor for lung cancer in women: data from the Women’s interagency HIV study. J Clin Oncol. 2010;28(9):1514–9.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Dubrow R, Silverberg MJ, Park LS, Crothers K, Justice AC. HIV infection, aging, and immune function: implications for cancer risk and prevention. Curr Opin Oncol. 2012;24(5):506.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Kesselring A, Gras L, Smit C, van Twillert G, Verbon A, de Wolf F, Reiss P, Wit F. Immunodeficiency as a risk factor for non–AIDS-defining malignancies in HIV-1–infected patients receiving combination antiretroviral therapy. Clin Infect Dis. 2011;52(12):1458–65.View ArticlePubMedGoogle Scholar
  34. Duncan KC, Chan KJ, Chiu CG, Montaner JS, Coldman AJ, Cescon A, Au-Yeung CG, Wiseman SM, Hogg RS, Press NM. HAART slows progression to anal cancer in HIV-infected MSM. AIDS. 2015;29(3):305–11.View ArticlePubMedGoogle Scholar
  35. Kowalkowski MA, Mims MA, Day RS, Du XL, Chan W, Chiao EY. Longer duration of combination antiretroviral therapy reduces the risk of Hodgkin lymphoma: a cohort study of HIV-infected male veterans. Cancer Epidemiol. 2014;38(4):386–92.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Krishnan S, Schouten JT, Jacobson DL, Benson CA, Collier AC, Koletar SL, Santana J, Sattler FR, Mitsuyasu R. Incidence of non-AIDS-defining cancer in antiretroviral treatment-naive subjects after antiretroviral treatment initiation: an ACTG longitudinal linked randomized trials analysis. Oncology. 2011;80(1–2):42–9.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Borges AH, Dubrow R, Silverberg MJ. Factors contributing to risk for cancer among HIV-infected individuals, and evidence that earlier combination antiretroviral therapy will alter this risk. Curr Opin HIV AIDS. 2014;9(1):34–40.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Kowalkowski MA, Day RS, Du XL, Chan W, Chiao EY. Cumulative HIV viremia and non-AIDS-defining malignancies among a sample of HIV-infected male veterans. J Acquir Immune Defic Syndr. 2014;67(2):204.View ArticlePubMedPubMed CentralGoogle Scholar
  39. Burgi A, Brodine S, Wegner S, Milazzo M, Wallace MR, Spooner K, Blazes DL, Agan BK, Armstrong A, Fraser S, et al. Incidence and risk factors for the occurrence of non-AIDS-defining cancers among human immunodeficiency virus-infected individuals. Cancer. 2005;104(7):1505–11.View ArticlePubMedGoogle Scholar
  40. Petoumenos K, van Leuwen MT, Vajdic CM, Woolley I, Chuah J, Templeton DJ, Grulich AE, Law MG. Cancer, immunodeficiency and antiretroviral treatment: results from the Australian HIV observational database (AHOD). HIV Med. 2013;14(2):77–84.View ArticlePubMedGoogle Scholar
  41. Vogel M, Friedrich O, Luchters G, Holleczek B, Wasmuth JC, Anadol E, Schwarze-Zander C, Nattermann J, Oldenburg J, Sauerbruch T, et al. Cancer risk in HIV-infected individuals on HAART is largely attributed to oncogenic infections and state of immunocompetence. Eur J Med Res. 2011;16(3):101–7.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© The Author(s). 2017