Skip to main content

Table 1 Summary table with variables from included studies

From: Breast cancer screening in sub-Saharan Africa: a systematic review and ethical appraisal

Author (year), country

Screening protocol, interval, longest follow-up

Participants, n study group ; control group

Age at enrollment (years)

Relevant screening outcomes metrics measured and findings

Apffelstaedt [18] (2008), RSA

Mammography, retrospective review of a prospective cohort of opportunistic mammography screening

Interval: NR

Longest follow-up: NR

7638

Age ≥ 40

Cancer cases diagnosed: 7.2/1000 examinations

Abuidris [19]

(2013), Sudan

CBE, conducted by trained local volunteers chosen from the community, using a cluster randomized design

Interval: NR

Longest follow-up: 34 months

14,788; 24,550

Age ≥ 18

Cancer cases diagnosed: 9 malignant + 8 DCIS (per 10,309 in the study group) vs 3 + 0 respectively control group; ~  < 1/1000 examinations

Brakohiapa [20] (2013), Ghana

Mammography, retrospective review of opportunistic mammography screening

Interval: NR

Longest follow-up: 1 year

106

NR

Cancer cases diagnosed: 6 IDC and 0 DCIS in the mammography screening group; ~ 56/1000 examinations

Luyeye Mvila [21]

(2014), DRC

CBE, conducted by trained healthcare professionals, as part of a breast awareness campaign

Interval: NR

Longest follow-up: 34 months

4315 (CBE); 1113 (mammography)a

Age ≥ 18

Cancer cases diagnosed: 87 malignant + 13 DICS;

Stage shifting: 24% Stage I & II; 75% stage III

Apffelstaedt [22] (2014), RSA

Mammography, utilizing opportunistic screening in a mobile breast screening unit

Interval: NR

Longest follow-up: 18 months

2712

Age ≥ 40

Cancer cases diagnosed: 3.71/1000 examinations

Apffelstaedt [23] (2014), RSA

Mammography, retrospective review of a prospective cohort of opportunistic mammography screening

Interval: NR

Longest follow-up: NR

3774

Age ≥ 40

Cancer cases diagnosed: 11.4/1000 examinations

Ngoma [24] (2015), Tanzania

CBE, conducted by trained lay personnel

in a cluster randomized design

Interval: annually

Longest follow-up: 3 years

Y1 6686; 3915b

Y2 6534; 3915

Y3 6241; 3915

NR

Stage Shifting: Stage I&II in year 1,2 & 3 in the study group vs control group = 0,%, 33%, 50% (p = NS) vs 9%, 60%, 67% (p = 0.021)

Total expenditure: $45,000 / year

Gutnik [25] (2016), Malawi

CBE, conducted by trained laywomen as breast health workers (BHW), in the clinic setting

Screening interval: NR

Longest follow-up: NR

1000

Age > 30

Cancer cases diagnosed*: 2 per 1000 examinations

PPV of CBE exam: 48% for BHW compared to physician exam

Sayed [26] (2016), Kenya

CBE, conducted by healthcare professionals in “breast awareness camps in the hospital setting

Screening interval: NR

Longest follow-up: NR

833

Age ≥ 15

Cancer cases diagnosed: 2 per 1000 exams in asymptomatic women

Omidiji [27]

(2017), Nigeria

Mammogram vs ultrasound, conducted by radiologists. self-controlled cross-sectional design

Screening interval: NR

Longest follow-up: NR

300

Age 30—60

Cancer cases diagnosed: 1 IDC and 6 DCIS per 300 asymptomatic women; 3.3 per 1000 examinations

Positive predictive value: 33.3% for ultrasound compared with mammogram

Pinder [28] (2018), Zambia

CBE, conducted by trained healthcare professionals

Interval: NR

Longest follow-up: NR

1955

NR

Cancer cases diagnosed: < 1% diagnosed with invasive cancer (17/1955); ~ 8.7 / 1000 examinations

Ginsberg [29]

(2012), SSA

Mammography, cost effectiveness of mammography screening in a mathematically modelling study using WHO-CHOICE methods

Interval: biennial

Longest follow-up: NA

c

50—70

CEA: Biennial screening mammography + treatment of all stages cost between $Int2248 and $Int4596 per DALY averted

Zelle [30]

(2012), Ghana

CBE, conducted by trained community nurses and screening mammography in a mathematical modelling study using WHO-CHOICE methods

Interval: Biennial

Longest follow-up: NA

d

40–69 (CBE)

50–69; 40–69 (Mammography)

CEA: Biennial CBE in women aged 40–69 + treatment for all stages seems the most cost effective—$1299 per DALY averted

Ralaidovy (2018), Eastern SSA [31]

Mammography, using “Generalized Cost-Effectiveness Analysis”

Interval: Biennial

Longest follow-up: NA

e

50–69

ICER: Biennial mammography in women 50–69 linked with timely diagnosis and treatment at 95% coverage – I$485 per HLY gained

Birnbaum [32] (2018), E. Africa (Uganda)

CBE, combined with multiple treatment strategies to assess breast cancer outcomes

Interval: Annual

Longest follow-up: 10-year cumulative outcomes

f

30 – 49

50—69

ARR: 113 (per 100,000 women)

YLS: 418 (per 1000,000 women)

  1. Key: BHW breast health workers, NR not reported, PPV positive predictive value, CEA cost effectiveness analysis, IDC invasive ductal carcinoma, DCIS ductal carcinoma in situ, DALY disability-adjusted life years, HLY healthy life years, ARR absolute risk reduction, YLS years life saved
  2. aRespective proportions of screening vs diagnostic mammograms not reported
  3. bYear 1 represents the baseline population the study and control villages
  4. cRegional age-adjusted population estimates of breast cancer incidence, breast cancer prevalence. Percentage of prevalent cases treated, and background mortality rates were based on WHO Burden of Disease study estimates for 2000
  5. dPopulation of female based on global burden of disease 2004 update
  6. eIncidence estimates obtained from GLOBOCAN 2012
  7. fInternational Agency for Research on Cancer. C15 I-X: Raikai, Uganda (2003–07)