Long-term follow-up on HIV infected and non-infected women with cervical cancer from Tanzania: staging, access to cancer-directed therapies and associated survival in a real-life remote setting

Abstract

Background: Worldwide 85% of cervical cancer (CC) related deaths occur in low- and middle-income countries. Sub-Saharan Africa is burdend by an overlapping high incidence of CC as well as HIV infection, a risk factor for HPV associated disease progression. Recent upscaling of CC screening activities increased the number of CC diagnoses in a previous unscreened population. The aim of the 2H study was to follow up on women with CC in the context of available health care services in Tanzania in relation to their HIV infection status.

Methods: This longitudinal observational cohort study included women with histological confirmed CC from Mbeya, Tanzania, between 2013-2019. All women were referred for CC staging and cancer-directed therapies (CDT), including surgery and/or radio-chemotherapy, or palliative care. Annual follow-up focused on successful linkage to CDT, interventions and survival. We assessed factors on compliance, used Kaplan-Meier-Survivor functions to evaluate survival time and poisson regression models to calculate incidence rate ratios on mortality (IRR) two years after diagnosis.

Results: Overall, 270 women with CC (123 HIV infected) were included. Staging information, available in 185 cases, showed 84.9% presented with advanced stage disease (FIGO ≥ IIB), no difference was seen in respect to HIV status. HIV-infected women were 12 years younger at the time of cancer diagnosis (median age 44.8 versus 56.4 years, p < 0.001). Median follow up period was 11.9 months (range 0.2-67.2). Survival information, available in 231 cases, demonstrated for women diagnosed in early-stage disease a median survival time of 38.3 months, in advanced-stage 16.0 months and late-stage disease 6.5 months after diagnosis. Of all women, 42% received CDT or palliative support. HIV co-infection and education were associated with higher health care compliance. CDT was significantly associated with lower 2-year mortality rates (IRR 0.62, p = 0.004). HIV coinfection did not impact mortality rates after diagnosis.

Conclusion: High numbers of advanced and late staged CC were diagnosed, compliance to CDT was low. A beneficial impact of CDT on CC mortality could be demonstrated for local health care services. This study indicates challenges for successful linkage and supports an effective scale up of cancer care and treatment facilities.

Keywords: Cancer screening; Cancer-directed therapy (CDT); Cervical cancer; FIGO staging; HIV; Mortality; Tanzania.

Fig. 1

Participant flow. All women diagnosed with cervical cancer between 2013 and 2019 (n = 270) were included for baseline assessment. For those with at least one follow-up visit or available outcome tracing information (n = 231) longitudinal assessment was performed

Fig. 2

HIV infected and non-infected women according to age and stage of cancer disease. A Distribution, proportion, and number of cases by FIGO stage stratified by HIV infected and non-infected women. B Distribution and proportion of age groups at the time of cervical cancer diagnosis stratified by HIV infected and non-infected women. HIV infected women were 12 years younger than non-infected participants than HIV non-infected women (median age 44.8 vs. 56.4 years, p < 0.001). Despite this difference in age at diagnosis no difference in cancer stage at diagnosis was seen

Fig. 3

Numbers and proportions of participants receiving cancer-directed therapies (CDT) and palliative care by disease severity. Early-stage disease FIGO I to IIA, advanced stage disease FIGO IIB to IIIB, late-stage disease FIGO IV. No interventions indicate that participants did not receive or obtain any CDT nor palliative care as confirmed by tracing information

Fig. 4

Kaplan Meier survival by FIGO stages. Significant lower survival estimates were seen with higher FIGO stages (p < 0.001)

Fig. 5

Factors associated with 2-year cancer mortality.Shown as incidence rate ratios on death (IRR), calculated by robust Poisson regression. *Adjusted by FIGO stage