Health Equity: Addressing AI Bias Now or Trusting Trickle-Down Effects?
In breast cancer screening, there is a high need for the introduction of AI in both developed and emerging countries. We believe it is essential to introduce AI at an
early stage to provide higher quality screening to current patients, and to verify the fairness and establish a system to ensure fairness while introducing AI
afterwards.
Breast cancer is a disease for which early detection is critical, i.e., screening is important. Early detection can lead to,✓ Reduction of death, mainly after distant metastasis.
✓ Improvement of postoperative quality of life by treating small lesions in the early stage is expected.
✓ The number of patients with breast cancer increases from the ages of 30s and 40s. Various life events are concentrated in this age group. It is important to start
treatment at an early stage when there are more options.
1. In the case of Japan✓ There is a very large difference in accuracy between cities where checkups are performed (Figs. 1 and 2). Since newer equipment models are becoming more
widely used, it is difficult to imagine the influence of differences in equipment performance. It is thought that differences in performance arise in operation, i.e.,
in image-reading. →This indicates that the introduction of AI has the potential to reduce the negative impact of differences in reading ability.
✓ The accuracy of mammography is limited, and a large percentage of cancers are not detected by screening until they have advanced to a symptomatic stage (Fig.
3).The introduction of new medical equipment with higher performance other than mammography is desirable, but it will take time to develop screening
guidelines. Utilizing AI prior to guideline implementation could facilitate the widespread use of new medical devices.
2. In emerging countries
In developed countries, the number of breast cancer patients is known to increase as the number of births decreases. However, in emerging countries, thenumber of breast cancer patients began to increase before the medical infrastructure for treatment was in place, and the mortality rate per population has alreadyexceeded that of developed countries (Fig. 4). However, since mammography is a difficult device to detect cancer from images, the cost of training physicians toread mammograms is a major obstacle to the spread of screening. AI is one of the important means to remove the disincentive for the spread of screening.

3. Challenges and risks in implementing AI developed in developed countries for health screening in emerging countries
i. When developing a single global reading assistance AI, how should genetic diversity be considered in the population in which it is trained? The more diverse apopulation is, the more it should be included in the sample to be trained, but such research on breast cancer and genetic diversity is not well developed.
ii. When implementing country-specific AI, the issue of biased medical device review and approval bodies in the U.S., Europe, Japan, China, etc. will have animpact.
In conclusion, post-marketing surveillance after AI implementation is important.

a)
Number of cities

Fig. 1

Number of cities for each cancer detection rate in JPN(after extracting only those cities with little variation)

Worst 20 cities

地域保健・健康増進事業報告(健康増進編)市区町村表より

Best 20 cities

5-years average of cancer detection rate in each city [%]20212020
201920182017cancer detection
rate [%]

1.00

Worst 20 cities, in each yearc)
cancer detection
rate [%]b)
0.80
0.60
0.40
0.200.00

1.00

Best 20 cities, in each year

0.80
0.60
0.40
0.20
0.00

Each city

Each city

Cities with high and low detection rates are not statistical variations, but are divided into stable,
high-performing and low-performing cities over a 5-year period

Fig. 2

Ex. Northwest Chiba prefecture

ShiraiNarashino
Kamagaya
Urayasu
Abiko
Nagareyama
Matsudo
Noda
Ishikawa
Kashiwa
Funabashi

白井市

習志野市
鎌ケ谷市
浦安市
我孫子市
流山市松戸市

7 times

野田市
市川市
柏市

Cancer detection ratio（％）

Ave. 0.36

船橋市
0.00

0.20

0.400.60>0.50.80

Cancer detection ratio[%]（令和4年度地域保健・健康増進事業報告(健康増進編)市区町村表より）

0.36～0.5
0.2～0.36<0.2Fig. 3a)c)

Sensitivity of MRI and mammography
to detect breast cancer

Sensitivity of breast
cancer detection[%]

Detected by medical
checkup (unaware)

MRI

100

Detected by medical
checkup (aware)
Mammography

50

Patients found out
on their own.

0paper1

paper2

paper3Paper1: C Kuhl et al., J. Clin Oncol, Vol. 28, 2010, p.1450-1457.
Paper2: C Riedl et al., J. Clin Oncol, Vol. 33, 2015, p.1128-1135.
Paper3: A. Chiarelli, et al, JNCI J. Natl Cancer Inst., Vol.112, No.2, 2020, p.136-144.

b)

Number of cases of detection status
relative to mass size (cm)cancer detection rate（cancer/all examinee ）0.33%

Positive Predictive Value（cancer/Findings
requiring inspection）

5.62%（令和4年度地域保健・健康増進事業報告(健康増進編)市区町村表より）<0.5

0.5< <1.01.1< <2.0 2.1< <5.0 5.1< < 10mass size (cm)

From the Japanese Breast CancerAssociation Database 2020

Mammography cannot detect cancer with sufficient sensitivity
because the cancer is hidden behind the mammary glands.
This indicates that further performance improvement isdifficult, as PPV is already in use at a very low level. As aresult, many breast cancers are actually found after the stage
has advanced.

Fig. 4 Incident and Mortality of breast cancer in each country

Population over 100M

30
Less than
5K USD

CMR

NGA

Mortality ASRLess than
1K USD

CIV
MLI

GHA
KENMYS EGYMAR
AFGPAKZAF
COD MDG
NERVNM

BFAMOZ10BGD

YEM

AGO

IND

UGA UZBTZNIRN
MMR

PER

0POL

COL

RUS

GBR

BRA

CAN

AUS

USAESP

JPN

SAU

40

FRA

ITA

DEU

IDN

TUR

Less than
50K USD

AGR

MEX

CHN

0DZA

UKR
THA

Less than
10K USD

PHL

SYR

SDN

20IRQ

ETH

Population over 20M
Population over 3M

Over 50K USD
in GDP per capita

KOR

80

Incident ASR

120