An examination of colorectal cancer burden by socioeconomic status: evidence from GLOBOCAN 2018

Abstract

Aim and background

Colon and rectum (colorectal) cancer cause substantial mortality and morbidity worldwide. The management and control of a complex disease such as cancer cannot rely on the old strategy of “one disease one medicine” and must make a transition into new-age practices involving predictive, preventive, and personalized medicine (PPPM) at its core. Adoption of PPPM approach to cancer management at the policy level requires quantification of cancer burden at the country level. For this purpose, we examine the burden of colorectal cancer in 185 countries in 2018. Based on results, we discuss the opportunities presented by PPPM and challenges to be encountered while adopting PPPM for the treatment and prevention of colorectal cancer.

Data and methods

Age- and sex-wise estimates of colorectal cancer were procured from the GLOBOCAN 2018. The country- and region-wise burden of colorectal cancer in 185 countries was examined using all-age and age-standardized incidence and mortality estimates. Human development index (HDI) was employed as the indicator of socioeconomic status of a country. Mortality-to-incidence ratio (MIR) was employed as the proxy of 5-year survival rate.

Results

Globally, colorectal cancer claimed an estimated 880,792 lives (males 484,224; females 396,568) with 1.85 million new cases (males 1.03 million; females 823,303) were estimated to be diagnosed in 2018. Globally, the age-standardized incidence rate (ASIR) was 19.7/100,000, whereas age-standardized mortality rate (ASMR) recorded to be 16.3/100,000 in 2018. Age-standardized rates were the highest in developed countries led by Hungary with ASIR of 51.2/100,000 followed by South Korea with ASIR of 44.5/100,000. ASMR followed the patterns of ASIR with the highest ASMR recorded by Hungary (21.5 per 100,000) and Slovakia (20.4 per 100,000). Globally, MIR stood at 0.48, and among the countries recording more than 1000 cases, Nepal registered the highest MIR of 0.83 and the lowest was recorded by South Korea (0.27). The age-standardized rates exhibited nonlinear association with HDI, whereas MIR was negatively associated with HDI.

Conclusion

Colorectal cancer causes a substantial burden worldwide and exhibit a positive association with the socioeconomic status. With the aid of improving screening modalities, preventable nature of the disease (due to dietary and lifestyle risk factors) and improving treatment procedures, the burden of CRC can largely be curtailed. The high burden of CRC in developing countries, therefore, calls for effective prevention strategies, cost-effective screening, and early-stage detection, cost-effective predictive, and personalized treatment regime.

Introduction

Globally, the burden of communicable diseases has been falling, and mortality and morbidity due to noncommunicable diseases have been rising since the last three decades [1]. The burden of communicable diseases has been proved to be amenable to interventions such as vaccination, public hygiene, and improvement in basic healthcare infrastructure. This, however, is not true for noncommunicable diseases such as cancer which lack an easy solution as a vaccine to treat every kind of neoplasia. Colorectal cancer (CRC) is one of the amenable causes of death and also has been one of the leading cancer groups causing substantial mortality and morbidity worldwide [1, 2]. CRC was previously considered to be a disease of affluence, but as the countries are climbing up the development hierarchy, its burden has risen sharply in developing countries exemplified by surges in countries such as Japan, Singapore and China [3]. Although the CRC burden has been the greatest in developed countries and rising in developing ones, survival rates, which depend crucially upon the stage of diagnosis, are significantly different in countries with different socioeconomic level [4]. The heterogeneous patterns of incidence, mortality, and survival implicate a gap in cancer detection and treatment in countries as per their socioeconomic status.

The majority of colorectal neoplasia are adenocarcinomas originating from epithelial cells of the colorectal mucosa; other rare types include neuroendocrine, squamous cell, adeno-squamous, spindle cell, and undifferentiated carcinomas [5]. Around 80–90% of newly diagnosed cases are sporadic with slow growth from adenomatous polyps to adenoma to adenocarcinoma while the rest (10–20%) is related to familial histories such as familial adenomatous polyposis (FAP) and hereditary nonpolyposis (HNPCC) [6]. The slow march of cancer from polyps to frank carcinoma can be arrested by employing screening methods such as stool-based procedures (e.g., fecal occult blood test and fecal immunochemical test) and structural examinations (e.g., colonoscopy, flexible sigmoidoscopy), thereby resulting in improved survival and low mortality rates [7].

Tackling the burden of a disease as complex as cancer requires new-age strategies such as predictive, preventive, and personalized medicine (PPPM) which is aiming to shift the focus of cancer therapeutics from reactive to a preventive and predictive one to provide individualized treatment paradigms to cancer patients [8–10]. In cancer management, this approach seeks to separate a healthy person from a patient, low-risk individual from the at-risk population, and a low-grade tumor from a high-grade tumor to offer precise and personalized medicine [8]. To devise proper cancer policy and implement PPPM strategies at the patient or provider level, it is pertinent to examine the recent estimates of the burden of cancer-in-question (CRC here) at the macro-level.

In this study, we examined the CRC burden using estimates from GLOBOCAN 2018 which produced country-, age-, and sex-wise estimates of the incidence, mortality, and prevalence of colorectal carcinoma in 185 countries for the year 2018 [11]. The socioeconomic status of a nation was gauged using country-level human development index (HDI)—a summary indicator of income, education, and longevity [12]. Five-year survival rate due to CRC was proxied using mortality-to-incidence ratio (MIR) which has been employed as the proxy of survival rates before [13–16]. An examination of CRC burden is expected to aid policy making and devise appropriate policy interventions to tackle a public health threat that is growing but is also amenable to prevention and early detection.

Data and methods

We procured the estimates of CRC burden from GLOBOCAN 2018, which provided age-, sex-, and country-wise incidence, mortality, and prevalence estimates of 36 neoplasia for 185 countries for the year 2018 [11, 17]. GLOBOCAN 2018 provided incidence and mortality estimates for each cancer group for 21 regions defined by United Nations Population Division (UNPD) in 18 nonoverlapping age groups (0–4, 5–9, 10–14, 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49, 50–54, 55–59, 60–64, 65–69, 70–74, 75–79, 80–84, and > 85 years). The complete GLOBOCAN 2018 estimation framework and calculation of various population health metrics are detailed elsewhere [11, 17]. The full set of GLOBOCAN 2018 results is available in the Global Cancer Observatory (http://gco.iarc.fr [18]). We procured data of CRC encoded as C18-C21 (colon, rectum, and anus) as per International Classification of Diseases tenth revision (ICD-10). In this study, we examine the CRC burden in terms of all-age incidence and mortality along with age-standardized rates expressed in terms of 100,000 person-years. The age-standardized incidence rate (ASIR) of a country was calculated using following formula.

$${\mathit{\text{ASIR}}}_i={\sum }_j\frac{C_{\mathit{ij}}\ast P_{\mathit{ij}}\ast w_j}{{\mathit{TP}}_i}$$ 1

In the above equation, i indexes the country and j indexes the age group. C_ij denotes number of cases in jth age group in ith country, P_ij denotes population in ith country in jth age group, TP_i denotes total population of ith country and w_j is the weight of jth age group ascribed by world population reference standard. The age-standardized mortality rate (ASMR) for different countries was calculated similarly by replacing number of cases (C_ij) by number of deaths (D_ij) in equation 1.

The 5-year survival rate of CRC was proxied using mortality-to-incidence ratio (MIR), which was calculated as the ratio of all-age death counts to all-age incident cases. MIR has been previously employed as a proxy for 5-year survival rate in the case of different neoplasia [13–16]. While we report estimates for all 185 countries, we focus primarily on the heavily burdened countries and regions. In addition to examining the country-wise burden of colorectal carcinoma, we also examined its relationship with a country’s socioeconomic status measured using its human development index (HDI) [12, 19]. HDI, an indicator of human development constructed by United N ations Development Program (UNDP), is a summary index of three indicators: health (life expectancy at birth), education (mean years of schooling and expected number of years of schooling)1, and income (gross national income (GNI) per capita)[12]. Country-specific value for each of the indicators was rescaled by UNDP on 0 to 1 scale with 0 corresponding to the lowest value and 1 to the highest reported value of the variable and the final HDI of a country is calculated as the geometric mean of the three indicators [12] using the following equation:

$$\mathit{HDI}=\sqrt[3]{\mathit{II}\ast \mathit{EI}\ast \mathit{HI}}$$ 2

In the above equation, II is the income index, EI denotes the education index, and HI denotes the health index. As GLOBOCAN estimates were available for the year 2018, and HDI data was available for 2017, we extrapolated the values of HDI for the year 2018 using the country-specific HDI values in the years 2016 and 2017. It was done to make the HDI values consistent with the values of CRC burden in the year 2018. Data analysis was conducted using Python 3.6, MS Excel 2016, and Stata 13.0 statistical software.

Results

Globally, there were an estimated 1.85 million newly diagnosed CRC cases with ASIR estimated to be 19.7 per 100,000 person-years in 2018. Sex-wise, there were 1.03 million incident cases in males and 823,303 cases in females (Table 1). CRC claimed an estimated 880,792 lives in 2018, out of which there were 484,224 males and 396,568 females. The ASMR was estimated to be8.9 per 100,000 person-years in 2018. Region-wise, colorectal cancer burden was the highest in East Asia with 736,573 incident cases (males 426,342 and females 310,231) and 325,128 deaths (males 183,346 and females 141,782). In terms of all-age incidence, North America ranked second with 179,771 cases (93,898 males; 85,873 females) followed by central and eastern Europe with 164,998 (males 84,951 and females 80,047) cases. In terms of deaths, however, central and eastern Europe ranked second after East Asia with 94,545 deaths (males 48,025 and females 46,520). Country-wise, China ranked first with 521,490 cases and 247,563 deaths followed by the USA with 155,098 cases and 54,611 deaths in 2018 (Table 1).

Table 1.

Colon and rectum cancer burden in 185 countries, 2018

	Incidence			ASIR			Deaths			ASMR			MIR
Population	T	M	F	T	M	F	T	M	F	T	M	F	T	M	F
Australia/New Zealand	21,217	11,444	9773	36.7	41.7	32.1	7424	3893	3531	11.1	12.9	9.5	0.35	0.34	0.36
Australia	17,782	9643	8139	36.9	41.9	32.4	6131	3237	2894	10.9	12.8	9.2	0.34	0.34	0.36
New Zealand	3435	1801	1634	35.3	40.2	30.8	1293	656	637	12.1	13.4	10.9	0.38	0.36	0.39
Caribbean	10,886	5016	5870	17.9	17.9	17.8	6259	2898	3361	9.6	9.9	9.3	0.57	0.58	0.57
Bahamas	115	60	55	22.2	26.4	19.4	50	28	22	9.3	12.3	7.4	0.43	0.47	0.4
Barbados	219	118	101	38.9	50.3	28.8	101	53	48	16.6	21.4	12.4	0.46	0.45	0.48
Cuba	4238	1811	2427	17.6	16.1	18.9	2811	1228	1583	10.7	10.2	11.1	0.66	0.68	0.65
Dominican Republic	1489	730	759	13.4	13.9	12.9	858	428	430	7.4	7.9	6.9	0.58	0.59	0.57
France, Guadeloupe	183	89	94	19.8	21.2	18.5	104	61	43	9.4	13.1	6.4	0.57	0.69	0.46
France, Martinique	214	111	103	23.9	29	19.8	110	56	54	10.9	13.3	9	0.51	0.5	0.52
Haiti	949	406	543	10.8	9.9	11.7	656	267	389	7.5	6.7	8.3	0.69	0.66	0.72
Jamaica	953	380	573	24.9	21.3	28.2	467	186	281	11.2	9.8	12.4	0.49	0.49	0.49
Puerto Rico	1823	979	844	27.3	34.1	22.1	736	414	322	9.8	13.4	7.1	0.4	0.42	0.38
Saint Lucia	36	16	20	14.5	13.3	16	20	10	10	8	8.2	7.9	0.56	0.63	0.5
Trinidad and Tobago	381	191	190	19.4	21.5	17.5	188	96	92	9.3	10.8	8	0.49	0.5	0.48
Central America	19,520	9959	9561	11	12.1	10	9614	4910	4704	5.3	5.9	4.7	0.49	0.49	0.49
Belize	24	11	13	9.7	9.2	10	15	7	8	6.3	6.2	6.3	0.63	0.64	0.62
Costa Rica	1128	560	568	16.7	17.6	15.9	617	316	301	8.6	9.5	7.7	0.55	0.56	0.53
El Salvador	681	267	414	9	8.9	9.1	367	143	224	4.6	4.5	4.7	0.54	0.54	0.54
Guatemala	802	368	434	6.3	6.3	6.3	450	206	244	3.5	3.5	3.4	0.56	0.56	0.56
Honduras	573	286	287	8.2	9	7.6	340	175	165	4.5	4.9	4.1	0.59	0.61	0.57
Mexico	14,900	7795	7105	11.2	12.5	10	7084	3719	3365	5.2	5.9	4.6	0.48	0.48	0.47
Nicaragua	631	250	381	11.3	10.2	12.2	367	145	222	6.5	5.9	6.9	0.58	0.58	0.58
Panama	781	422	359	16.2	18.5	14.1	374	199	175	7.4	8.4	6.5	0.48	0.47	0.49
Central and Eastern Europe	164,998	84,951	80,047	28.8	37.5	23.2	94,545	48,025	46,520	15.2	20.5	11.9	0.57	0.57	0.58
Belarus	5680	2802	2878	31.8	41.6	26	2919	1315	1604	15.1	19.2	12.8	0.51	0.47	0.56
Bulgaria	4604	2724	1880	28.5	38.3	20.7	2714	1642	1072	14.9	21.3	10	0.59	0.6	0.57
Czechia	7838	4538	3300	32.7	42.5	24.9	3421	1974	1447	12.7	17.4	9.1	0.44	0.43	0.44
Hungary	10,809	6115	4694	51.2	70.6	36.8	5076	2867	2209	21.5	31.2	14.8	0.47	0.47	0.47
Moldova	2171	1241	930	34.2	47.3	25.2	1202	699	503	18.7	26.9	13.2	0.55	0.56	0.54
Poland	24,507	14,027	10,480	30.3	41.1	22.1	14,362	8104	6258	16.1	22.6	11.4	0.59	0.58	0.6
Romania	11,076	6500	4576	26.7	36.3	19.3	6319	3702	2617	13.7	19.2	9.5	0.57	0.57	0.57
Russian Federation	71,406	33,095	38,311	26.7	32.9	23.2	42,349	19,430	22,919	14.7	18.9	12.3	0.59	0.59	0.6
Slovakia	4624	2724	1900	43.8	60.7	31.2	2396	1376	1020	20.4	29.5	14.4	0.52	0.51	0.54
Ukraine	22,283	11,185	11,098	25.8	33.6	21.1	13,787	6916	6871	15.1	20.3	11.9	0.62	0.62	0.62
Eastern Africa	17,125	7933	9192	7.7	7.8	7.7	12,201	5802	6399	5.7	6	5.5	0.71	0.73	0.7
Burundi	418	193	225	8.3	7.7	8.8	357	166	191	7.4	7	7.6	0.85	0.86	0.85
Comoros	18	8	10	4.3	4.1	4.5	18	8	10	4.3	4.1	4.5	1	1	1
Djibouti	41	20	21	5.6	5.8	5.5	34	18	16	4.9	5.4	4.4	0.83	0.9	0.76
Eritrea	189	95	94	6.3	7	5.8	149	77	72	5.2	5.9	4.7	0.79	0.81	0.77
Ethiopia	4716	2206	2510	7.5	7.8	7.4	3555	1745	1810	5.8	6.3	5.5	0.75	0.79	0.72
France, La Réunion	349	186	163	25.2	29.2	21.6	143	72	71	9.3	10.9	7.9	0.41	0.39	0.44
Kenya	2316	1134	1182	9.3	10	8.7	1466	738	728	6	6.8	5.4	0.63	0.65	0.62
Madagascar	827	366	461	6.1	5.5	6.5	579	258	321	4.4	4.2	4.7	0.7	0.7	0.7
Malawi	354	171	183	3.5	3.9	3.3	239	119	120	2.5	2.9	2.2	0.68	0.7	0.66
Mauritius	288	156	132	14.7	17.4	12.6	173	92	81	8.6	10.3	7.1	0.6	0.59	0.61
Mozambique	561	278	283	3.3	3.7	3	451	224	227	2.8	3.2	2.5	0.8	0.81	0.8
Rwanda	838	355	483	13.4	12.6	14.1	592	258	334	9.8	9.7	10	0.71	0.73	0.69
Somalia	599	298	301	8	8.4	7.6	539	273	266	7.4	7.9	6.9	0.9	0.92	0.88
South Sudan	509	256	253	7.1	7.5	6.7	420	216	204	6	6.6	5.5	0.83	0.84	0.81
Tanzania	2594	1004	1590	9	7.4	10.4	1767	704	1063	6.3	5.5	7	0.68	0.7	0.67
Uganda	1345	655	690	8.1	8.3	7.9	961	458	503	6.2	6.4	5.9	0.71	0.7	0.73
Zambia	355	163	192	4.6	4.9	4.4	202	103	99	2.8	3.2	2.4	0.57	0.63	0.52
Zimbabwe	793	382	411	10.1	11.6	9.1	549	269	280	7.2	8.4	6.3	0.69	0.7	0.68
Eastern Asia	736,573	426,342	310,231	26.5	32	21.3	325,128	183,346	141,782	10.9	13.3	8.7	0.44	0.43	0.46
China	521,490	303,853	217,637	23.7	28.1	19.4	247,563	142,476	105,087	10.9	13.1	8.8	0.47	0.47	0.48
Japan	148,151	82,641	65,510	38.9	49.1	29.6	57,910	30,228	27,682	12	15.2	9.2	0.39	0.37	0.42
North Korea	6566	3266	3300	18.8	22.7	15.8	3112	1415	1697	8.5	10.4	7.3	0.47	0.43	0.51
South Korea	42,363	26,143	16,220	44.5	59.5	31.3	9762	5445	4317	8.7	11.8	6.3	0.23	0.21	0.27
Mongolia	146	67	79	6.2	6.5	6	88	42	46	3.8	4	3.6	0.6	0.63	0.58
Melanesia	906	557	349	12.8	17.8	9	561	372	189	8.1	12.3	4.9	0.62	0.67	0.54
Fiji	86	43	43	10.1	11.3	9.3	50	27	23	6.2	7.9	5.2	0.58	0.63	0.53
France, New Caledonia	101	59	42	25.8	31.7	20.5	34	23	11	9	13	5.6	0.34	0.39	0.26
Papua New Guinea	684	439	245	13	19.3	8.4	447	307	140	8.7	14	4.8	0.65	0.7	0.57
Solomon Islands	25	12	13	7	7.3	6.6	21	11	10	5.9	6.7	5.1	0.84	0.92	0.77
Vanuatu	10	4	6	5.1	4.3	5.9	9	4	5	4.6	4.3	5	0.9	1	0.83
Micronesia	96	55	41	17.4	20.9	13.9	51	31	20	9.5	12.5	6.8	0.53	0.56	0.49
Guam	38	21	17	17.2	20.1	14.6	20	12	8	9.1	11.6	7.1	0.53	0.57	0.47
Middle Africa	6010	2895	3115	7.5	7.8	7.3	4562	2232	2330	5.9	6.3	5.6	0.76	0.77	0.75
Angola	733	374	359	5.3	6	4.8	480	254	226	3.6	4.3	3.1	0.65	0.68	0.63
Cameroon	871	450	421	6.9	7.7	6.3	609	322	287	5	5.8	4.4	0.7	0.72	0.68
Central African Republic	151	78	73	5.8	6.5	5.2	139	73	66	5.4	6.3	4.8	0.92	0.94	0.9
Chad	413	214	199	5.9	6.6	5.3	325	169	156	5	5.6	4.5	0.79	0.79	0.78
Congo	152	81	71	5	5.7	4.5	102	56	46	3.5	4.1	3	0.67	0.69	0.65
Democratic Republic of Congo	3568	1627	1941	9.1	9	9.2	2831	1314	1517	7.4	7.5	7.3	0.79	0.81	0.78
Equatorial Guinea	40	24	16	5.8	6.4	5.2	30	18	12	5	5.8	4.2	0.75	0.75	0.75
Gabon	82	47	35	5.5	6.3	4.9	46	26	20	3.3	3.8	3	0.56	0.55	0.57
Sao Tome and Principe	5	3	2	6.6	9.5	4.4	3	2	1	4.1	6.6	2.2	0.6	0.67	0.5
North America	179,771	93,898	85,873	26.2	29.5	23.2	64,121	33,752	30,369	8.4	9.9	7.1	0.36	0.36	0.35
Canada	24,617	13,039	11,578	31.5	35.2	28	9494	5086	4408	10.1	12.2	8.2	0.39	0.39	0.38
USA	155,098	80,829	74,269	25.6	28.8	22.6	54,611	28,658	25,953	8.2	9.6	6.9	0.35	0.35	0.35
Northern Africa	18,810	9696	9114	9.2	10	8.6	10,902	5801	5101	5.4	6.1	4.7	0.58	0.6	0.56
Algeria	5537	2910	2627	13.9	14.8	13	3027	1684	1343	7.5	8.5	6.6	0.55	0.58	0.51
Egypt	5393	2661	2732	6.5	6.6	6.3	3041	1487	1554	3.7	3.8	3.5	0.56	0.56	0.57
Libya	675	309	366	12.6	13	12.5	404	192	212	8	8.5	7.6	0.6	0.62	0.58
Morocco	4118	2205	1913	10.9	12.2	9.8	2462	1381	1081	6.5	7.7	5.4	0.6	0.63	0.57
Sudan	1398	746	652	5.4	6.2	4.7	1004	555	449	3.9	4.7	3.3	0.72	0.74	0.69
Tunisia	1657	848	809	11.9	13	11	950	493	457	6.6	7.5	5.9	0.57	0.58	0.56
Northern Europe	75,900	41,255	34,645	32.1	37.5	27.3	32,659	17,367	15,292	11.2	13.5	9.3	0.43	0.42	0.44
Denmark	5585	2966	2619	41	45.9	36.6	1934	1003	931	12	13.7	10.5	0.35	0.34	0.36
Estonia	942	416	526	29.2	34.8	25.9	482	234	248	12.5	17.8	9.5	0.51	0.56	0.47
Finland	3440	1826	1614	24.6	28.7	21.2	1393	755	638	8.6	10.8	6.8	0.4	0.41	0.4
Iceland	168	92	76	26.2	30.5	22	82	46	36	10.9	13.4	8.6	0.49	0.5	0.47
Ireland	2968	1752	1216	34	42.4	26.4	1207	686	521	12.2	15.2	9.7	0.41	0.39	0.43
Latvia	1550	735	815	33	42.6	27.7	706	321	385	12.8	17.3	10.4	0.46	0.44	0.47
Lithuania	1831	898	933	27.2	35.6	22.1	996	535	461	12.8	19.6	8.9	0.54	0.6	0.49
Norway	4887	2530	2357	42.9	46.9	39.3	1750	915	835	13.2	15.3	11.3	0.36	0.36	0.35
Sweden	6421	3370	3051	26.9	29.7	24.3	3062	1637	1425	10.6	12.4	9	0.48	0.49	0.47
UK	47,892	26,551	21,341	32.1	37.8	27	20,957	11,186	9771	11.1	13.3	9.3	0.44	0.42	0.46
Polynesia	113	67	46	16.2	20	12.4	30	23	7	4.4	7.4	2.1	0.27	0.34	0.15
French Polynesia	47	27	20	13.9	15.9	11.6	11	9	2	3.4	5.6	1.2	0.23	0.33	0.1
Samoa	37	24	13	22.6	30.6	14.8	13	8	5	7.8	10.9	6.3	0.35	0.33	0.38
South America	97,600	48,061	49,539	18.6	20.6	17.1	48,793	24,563	24,230	8.9	10.3	7.8	0.5	0.51	0.49
Argentina	15,692	8527	7165	25	31.5	20.2	8721	4751	3970	12.6	16.6	9.8	0.56	0.56	0.55
Bolivia	605	311	294	6.1	6.7	5.6	371	194	177	3.7	4.1	3.2	0.61	0.62	0.6
Brazil	51,783	24,737	27,046	19.6	21.1	18.6	24,482	12,031	12,451	9	10.1	8.1	0.47	0.49	0.46
Chile	5914	3002	2912	20.7	23.9	18.2	3144	1556	1588	10.2	11.9	8.9	0.53	0.52	0.55
Colombia	9140	4396	4744	15.8	16.9	15	4489	2203	2286	7.6	8.4	6.9	0.49	0.5	0.48
Ecuador	2025	902	1123	11.3	10.8	11.7	1100	507	593	5.8	5.9	5.8	0.54	0.56	0.53
French Guyana	54	32	22	21.7	26.8	17	14	8	6	5.8	7.3	4.3	0.26	0.25	0.27
Guyana	36	15	21	5	4.4	5.4	27	12	15	3.8	3.5	3.9	0.75	0.8	0.71
Paraguay	895	466	429	13.9	15	12.7	552	284	268	8.3	9	7.5	0.62	0.61	0.62
Peru	4610	2255	2355	13.3	14.2	12.4	2367	1220	1147	6.5	7.5	5.7	0.51	0.54	0.49
Suriname	94	51	43	15.4	18.8	12.7	70	38	32	11.3	14.1	8.9	0.74	0.75	0.74
Uruguay	2273	1152	1121	35	43.8	28.3	1093	555	538	15	19.3	12.1	0.48	0.48	0.48
Venezuela	4479	2215	2264	13.6	14.8	12.6	2363	1204	1159	7.1	8.1	6.2	0.53	0.54	0.51
South-Eastern Asia	95,223	53,542	41,681	14.3	17.6	11.6	52,475	29,384	23,091	7.9	9.9	6.3	0.55	0.55	0.55
Brunei	140	84	56	35	43.4	27.4	50	32	18	13.9	18.5	9.8	0.36	0.38	0.32
Cambodia	1314	637	677	11.1	13	9.9	859	414	445	7.5	8.8	6.7	0.65	0.65	0.66
Indonesia	30,017	19,113	10,904	12.1	16.2	8.4	16,386	10,279	6107	6.9	9.3	4.8	0.55	0.54	0.56
Lao PDR	652	326	326	13.9	14.9	13.1	394	197	197	8.6	9.4	8	0.6	0.6	0.6
Malaysia	6137	3342	2795	19.9	22	17.9	3414	1863	1551	11.2	12.5	9.9	0.56	0.56	0.55
Myanmar	4751	2600	2151	9.1	11.1	7.6	2960	1606	1354	5.8	7.1	4.8	0.62	0.62	0.63
Philippines	15,680	8791	6889	18.9	23.5	15.2	8821	4841	3980	11	13.9	8.9	0.56	0.55	0.58
Singapore	4202	1994	2208	36.8	38.9	34	1980	1050	930	17.3	20.2	14.6	0.47	0.53	0.42
Thailand	17,534	9015	8519	15.5	17.6	13.9	9462	4963	4499	8.4	9.7	7.4	0.54	0.55	0.53
Timor-Leste	63	33	30	8.9	9.7	8.1	45	23	22	6.5	7.1	5.9	0.71	0.7	0.73
Viet Nam	14,733	7607	7126	13.4	16	11.6	8104	4116	3988	7	8.7	5.9	0.55	0.54	0.56
Southern Africa	7167	3637	3530	13.4	16.8	11.2	3801	1979	1822	7.1	9.5	5.7	0.53	0.54	0.52
Botswana	53	35	18	2.9	4.9	1.6	28	20	8	1.7	3.2	0.8	0.53	0.57	0.44
Eswatini	30	16	14	3.6	4.6	2.9	18	11	7	2.4	3.5	1.7	0.6	0.69	0.5
Lesotho	47	27	20	3.1	4.4	2.4	35	21	14	2.5	3.6	1.8	0.74	0.78	0.7
Namibia	100	51	49	6.3	7.3	5.5	56	29	27	3.6	4.3	3.1	0.56	0.57	0.55
South Africa	6937	3508	3429	14.4	18.1	12	3664	1898	1766	7.6	10.2	6.1	0.53	0.54	0.52
South-Central Asia	88,033	53,534	34,499	4.9	6.1	3.8	63,401	39,852	23,549	3.6	4.6	2.6	0.72	0.74	0.68
Afghanistan	805	487	318	4	4.7	3.4	709	436	273	3.7	4.2	3	0.88	0.9	0.86
Bangladesh	5549	3164	2385	3.8	4.3	3.3	4469	2605	1864	3	3.5	2.6	0.81	0.82	0.78
Bhutan	30	23	7	4.2	6	2.1	24	19	5	3.7	5.5	1.6	0.8	0.83	0.71
India	56,751	36,687	20,064	4.4	5.8	3.1	43,090	28,591	14,499	3.4	4.6	2.2	0.76	0.78	0.72
Iran	9864	5630	4234	12.9	14.6	11.1	4153	2395	1758	5.6	6.3	4.8	0.42	0.43	0.42
Kazakhstan	3049	1392	1657	15.4	17.7	14.1	2108	1023	1085	10.5	13.3	8.9	0.69	0.73	0.65
Kyrgyzstan	352	174	178	7.3	8.1	6.5	274	136	138	5.7	6.4	5	0.78	0.78	0.78
Maldives	41	30	11	11.9	15.9	7.2	20	17	3	6.3	10.5	1.8	0.49	0.57	0.27
Nepal	1432	514	918	5.8	4.4	7	1191	449	742	4.8	3.9	5.7	0.83	0.87	0.81
Pakistan	6475	3587	2888	4.2	4.5	3.8	5003	2822	2181	3.3	3.7	3	0.77	0.79	0.76
Sri Lanka	1441	734	707	5.2	5.8	4.7	968	518	450	3.4	4	2.9	0.67	0.71	0.64
Tajikistan	263	165	98	4	4.9	3.1	207	131	76	3.1	4	2.4	0.79	0.79	0.78
Turkmenistan	278	134	144	6	6.7	5.6	168	87	81	3.7	4.2	3.2	0.6	0.65	0.56
Uzbekistan	1703	813	890	6.3	6.5	6	1017	623	394	3.8	5.1	2.7	0.6	0.77	0.44
Southern Europe	119,949	69,446	50,503	31.6	40.4	24.1	53,975	30,991	22,984	11.5	15.4	8.4	0.45	0.45	0.46
Albania	402	225	177	8.4	9.6	7.2	198	115	83	3.7	4.5	3	0.49	0.51	0.47
Bosnia and Herzegovina	1818	1046	772	26.1	33	20.4	1081	628	453	13.3	18.2	9.4	0.59	0.6	0.59
Croatia	3387	1951	1436	34.1	45.9	24.9	2187	1288	899	18.9	27.4	12.7	0.65	0.66	0.63
Greece	7319	4158	3161	26.2	32.3	21.1	3430	1985	1445	9.7	12.7	7.3	0.47	0.48	0.46
Italy	49,327	26,930	22,397	29.9	36	24.8	21,172	11,491	9681	10.2	12.8	8	0.43	0.43	0.43
Macedonia FYR	996	517	479	28.4	30.9	26.3	472	248	224	12.5	14.2	11.1	0.47	0.48	0.47
Malta	302	180	122	29.1	36	23.2	121	70	51	10.6	13.2	8.6	0.4	0.39	0.42
Montenegro	210	115	95	18.6	22.7	14.9	115	62	53	9.2	11.2	7.5	0.55	0.54	0.56
Portugal	10,270	6104	4166	40	54	28.7	4261	2497	1764	13.5	18.7	9.6	0.41	0.41	0.42
Serbia	6149	3775	2374	36.7	49	26.4	3232	1966	1266	16.8	23.3	11.6	0.53	0.52	0.53
Slovenia	1987	1301	686	41.1	58.9	25.5	740	423	317	12.5	17.1	8.9	0.37	0.33	0.46
Spain	37,172	22,744	14,428	33.4	45.2	23.3	16,683	10,038	6645	12	16.8	8	0.45	0.44	0.46
Western Africa	12,734	6489	6245	6.4	6.8	6.1	8568	4440	4128	4.5	4.9	4.2	0.67	0.68	0.66
Benin	433	274	159	6.8	9.5	4.6	299	190	109	4.8	6.8	3.2	0.69	0.69	0.69
Burkina Faso	583	243	340	6.3	5.5	6.7	463	194	269	5.3	4.8	5.6	0.79	0.8	0.79
Cabo Verde	30	9	21	6.4	7.3	6.3	21	6	15	4.2	4.2	4.3	0.7	0.67	0.71
Côte d’Ivoire	737	333	404	5.8	4.9	6.9	552	259	293	4.5	3.9	5.2	0.75	0.78	0.73
Gambia	11	9	2	1.1	1.7	0.48	9	7	2	0.98	1.5	0.48	0.82	0.78	1
Ghana	1228	658	570	7.8	9.6	6.6	824	467	357	5.5	7.1	4.2	0.67	0.71	0.63
Guinea	145	77	68	2	2.1	1.8	118	65	53	1.7	1.9	1.5	0.81	0.84	0.78
Guinea-Bissau	61	30	31	6.1	7.1	5.5	53	28	25	5.6	6.9	4.7	0.87	0.93	0.81
Liberia	102	43	59	3.9	3.4	4.3	84	37	47	3.4	3	3.6	0.82	0.86	0.8
Mali	917	385	532	10.5	9	11.7	686	290	396	8.3	7.3	9.1	0.75	0.75	0.74
Mauritania	159	70	89	6.1	5.2	6.7	111	48	63	4.5	3.8	4.9	0.7	0.69	0.71
Niger	583	305	278	5.3	5.5	5	522	284	238	4.9	5.3	4.5	0.9	0.93	0.86
Nigeria	6692	3568	3124	6.2	6.8	5.6	4059	2202	1857	4	4.5	3.5	0.61	0.62	0.59
Senegal	529	226	303	6.5	6.3	6.6	372	165	207	4.8	4.9	4.7	0.7	0.73	0.68
Sierra Leone	216	103	113	5.5	5	5.9	173	83	90	4.7	4.3	5	0.8	0.81	0.8
Togo	303	153	150	7.2	7.2	7.1	219	113	106	5.5	5.6	5.3	0.72	0.74	0.71
Western Asia	38,067	21,490	16,577	16.3	19.4	13.6	20,418	11,240	9178	8.7	10.4	7.3	0.54	0.52	0.55
Armenia	990	367	623	19.9	18.4	20.8	640	252	388	12.4	12.6	12.1	0.65	0.69	0.62
Azerbaijan	1114	668	446	10.2	13.8	7.4	774	482	292	7.1	10.2	4.8	0.69	0.72	0.65
Bahrain	120	72	48	12.6	14.2	11.2	70	40	30	8.1	8.9	7.6	0.58	0.56	0.63
Cyprus	511	338	173	24.2	34.4	15.3	242	154	88	10.2	14.6	6.5	0.47	0.46	0.51
West Bank and Gaza Strip	501	262	239	19.1	21.1	17.3	303	159	144	11.9	13.3	10.7	0.6	0.61	0.6
Georgia	645	331	314	8.7	11.1	7.1	427	226	201	5.7	7.5	4.4	0.66	0.68	0.64
Iraq	1391	763	628	6.1	7.2	5.2	813	446	367	3.7	4.4	3.1	0.58	0.58	0.58
Israel	2519	1336	1183	20.1	22.8	18	1390	717	673	9.3	11	7.9	0.55	0.54	0.57
Jordan	1105	460	645	17	14.8	19.2	589	257	332	9.3	8.5	10	0.53	0.56	0.51
Kuwait	352	195	157	13.2	12.9	14	178	97	81	7.5	7.4	7.9	0.51	0.5	0.52
Lebanon	1463	775	688	20	20.8	19.2	851	451	400	10.9	11.7	10.3	0.58	0.58	0.58
Oman	368	262	106	11	11.7	9.6	195	137	58	6.4	6.8	5.6	0.53	0.52	0.55
Qatar	142	100	42	13	13.5	13.8	79	54	25	8.7	9	9.5	0.56	0.54	0.6
Saudi Arabia	3564	2405	1159	13.1	14.9	10.6	1603	1077	526	6.3	7.3	5	0.45	0.45	0.45
Syrian Arab Republic	1890	870	1020	14.4	14.3	14.5	1248	583	665	9.5	9.7	9.4	0.66	0.67	0.65
Turkey	20,031	11,548	8483	21	27.4	16	10,033	5571	4462	10.2	13.1	7.9	0.5	0.48	0.53
United Arab Emirates	662	437	225	14.1	14.8	13.5	314	207	107	7.4	7.7	7.3	0.47	0.47	0.48
Yemen	1210	639	571	8.6	9.5	7.8	911	484	427	6.7	7.5	6	0.75	0.76	0.75
Western Europe	138,820	75,948	62,872	28.8	34.5	23.7	61,304	33,323	27,981	10.3	13.1	8	0.44	0.44	0.45
Austria	4421	2531	1890	20.7	26.3	16.1	2276	1318	958	8.9	12	6.2	0.51	0.52	0.51
Belgium	9346	5266	4080	35.3	43.8	28	3224	1669	1555	9.7	11.9	7.8	0.34	0.32	0.38
France	47,025	25,813	21,212	30.4	36.9	24.8	19,962	10,821	9141	10.2	13.1	7.9	0.42	0.42	0.43
Germany	58,047	31,026	27,021	26.2	31	22.1	27,334	14,931	12,403	10.1	13	7.7	0.47	0.48	0.46
Luxembourg	323	170	153	28.1	31.4	25.3	134	72	62	10.1	12.3	8.1	0.41	0.42	0.41
Netherlands	14,921	8513	6408	37.8	45.3	31.1	6442	3443	2999	13.8	16.5	11.5	0.43	0.4	0.47
Switzerland	4681	2598	2083	24	28.4	20.2	1909	1054	855	8.1	10.1	6.4	0.41	0.41	0.41
World	1,849,518	1,026,215	823,303	19.7	23.6	16.3	880,792	484,224	396,568	8.9	10.8	7.2	0.48	0.47	0.48
t Test (male vs female)		2.20** (0.014)			10.27*** (0.000)			2.14** (0.016)			12.29*** (0.000)			5.00*** (0.000)

T: Total, both sexes, all age-groups; F: Females, all age-groups; M: Males, all age-groups; ASIR: age-standardized incidence rate per 100,000 person-years; ASMR: age-standardized mortality rate per 100,000 person-years; MIR: Mortality-to-incidence ratio. Data Source: GLOBOCAN 2018 (IARC). T-test in the last column tests for the hypothesis of M (male mean) – F (female mean) = 0 against the one-sided alternate hypothesis M-F < 0; **/*** denotes statistical significance at 5%/1% respectively

Age-standardized rates were the highest in developed regions led by Australia/New Zealand region with ASIR of 36.7/100,000 followed by northern Europe with ASIR of 32.1/100,000. ASIR was the lowest in south-central Asia at 4.9 per 100,000 person-years in 2018. ASMR was again the highest in central and eastern Europe (15.2/100,000) followed by southern Europe (11.5/100,000) with south-central Asia registering the lowest ASMR of 3.6/100,000 in 2018. Top-3 countries with highest ASIR were Hungary (51.2/100,000), South Korea (44.5 per 100,000) and Slovakia (43.8 per 100,000) in 2018 (Table 1; Fig. 1a). The estimated ASMR was again the highest in developed countries led by Hungary (21.5/100,000) and Slovakia (20.4 per 100,000) (Table 1; Fig. 1b). Among the countries with more than 1000 incident cases in 2018, ASIR varied 13-fold from Bangladesh with ASIR of 3.8/100,000 to 51.2/100,000 recorded by Hungary. ASMR varied 7-fold in these countries (> 1000 cases) ranging from Bangladesh with ASMR of 3.0/100,000 to Hungary which recorded ASMR of 21.5/100,000 in 2018.

Fig. 1.

Geographical distribution of colorectal cancer burden in both sexes in 2017. a ASIR. b ASMR. ASIR age-standardized incidence rate per 100,000 person-years, ASMR age-standardized mortality rate per 100,000 person-years. Data source: GLOBOCAN 2018 (IARC)

Sex-wise, we noted that CRC had more proclivity towards males than females with males recording ASIR of 23.8/100,000 as against female ASIR of 21.8/100,000. The male-female difference in ASIR was the greatest in European regions, e.g., Southern Europe, male ASIR 40.4/100,000 and female ASIR 24.1/100,000. Globally, the ASMR was again higher in males (10.8/100,000) than females (7.2/100,000). The male-female difference in ASMR was the highest in European regions, e.g., central and eastern Europe, male ASMR 20.5/100,000 and female ASMR 11.9/100,000. The pattern of male dominance in terms of CRC burden was preserved across other world regions with few of the heavily burdened countries recording male age-standardized rates approximately twice as that of female age-standardized rates; for instance, Poland has an estimated male ASMR of 22.6/100,000 and female ASMR of 11.4/100,000 (Table 1). The t test of mean difference between male and females across countries was again found to be significant across all the metrics (bottom row of Table 1).

Across the age groups, the CRC incidence exhibited bell-shaped distribution; deaths due to CRC, however, increased monotonically with age (Fig. 2). The male dominance in terms of CRC burden was again preserved across different age groups with each of them except the oldest (85 plus) registering higher incidence as well as the death counts in males than in females (Fig. 2).

Fig. 2.

Age-group and gender-wise burden of colon and rectum cancer in 2018. a Incidence. b Deaths. Data source: GLOBOCAN 2018 (IARC)

To examine the statistical relationship between CRC and HDI, we regressed ASIR and ASMR on HDI in linear form as well as by including the quadratic term (Table 2). The model including only the linear term of HDI could explain 58.7% variation in ASIR, whereas it explained 38.6% variation in ASMR. The inclusion of quadratic term resulted in a better fit of the model with regression involving both linear and quadratic term explaining 66.8% and 40.9% variation in ASIR and ASMR, respectively. CRC was generally higher in developed countries with a sharp upsurge in the positive relationship at HDI around 0.5 and 0.37 with the nonlinearity not as sharp in case of ASMR as it was in the case of ASIR (Table 2, Fig. 3).

Table 2.

Association between human development and indicators of CRC burden

	ASIR as dependent Variable		ASMR as dependent Variable		MIR as dependent Variable
HDI	56.9*** (3.4)	− 134.8*** (22.9)	16.1*** (1.3)	− 20.8* (11.0)	− 0.7839*** (0.0324)	− 0.6718** (0.2833)
HDI SQ		140.5*** (17.5)		27.0*** (8.1)		− 0.0821 (0.2108)
Intercept	− 24.0*** (2.3)	38.0*** (7.1)	− 3.4*** (0.9)	8.6*** (3.5)	1.1504*** (0.0239)	1.1142*** (0.0900)
R2	0.5869	0.6691	0.3850	0.4101	0.7240	0.7242
Turning Point		0.4797		0.3852

Data source: MIR was calculated directly as the ratio of all-age death numbers and no. of all-age incident cases which were procured from GLOBOCAN 2018 (IARC) and HDI estimates from UNDP. Robust standard errors are presented inside parenthesis

ASMR age-standardized mortality rate per 100,000 person-years, both sexes, ASIR age-standardized incidence rate per 100,000 person-years, both sexes, MIR mortality-to-incidence ratio, HDI country-wise human development index

*, **, *** represent statistical significance at 10, 5, and 1% level of significance. Turning point is calculated as $\frac{-{\beta }_1}{2{\beta }_2}$

Fig. 3.

Nonlinear relationship between human development and age-standardized rates. a ASIR vs HDI. b ASMR vs HDI. c MIR vs HDI. ASMR age-standardized mortality rate per 100,000 person-years, both sexes, ASIR age-standardized incidence rate per 100,000 person-years, both sexes, MIR mortality-to-incidence ratio, HDI human development index. Data source: MIR was calculated directly as the ratio of all-age death numbers and no. of all-age incident cases, both of which were procured from GLOBOCAN 2018 (IARC) and HDI estimates were obtained from UNDP

MIR, a proxy indicator of 5-year survival rate, exhibited negative gradient with HDI (Fig. 3c). The global MIR of CRC stood at 0.48 with 140 countries recording MIR above the global MIR. Among the regions, the highest MIR (or the lowest survival rates) was recorded by African regions (middle Africa 0.76 and eastern Africa 0.71). The MIR was also high in south-central Asia at 0.71. Although ASIR was one of the highest in Australia/New Zealand region, its MIR was one of the lowest at 0.35. Among the countries with incidence greater than 1000 in 2018, MIR exhibited a 3.6-fold variation ranging from 0.23 in South Korea to 0.83 in Nepal. Unlike ASIR and ASMR, the pattern of association of MIR with HDI was found to be strictly linear and downward sloping rather than quadratic (Fig. 3c; Table 2). HDI could explain 72.6% of the variation in MIR (Table 2) with the inclusion of quadratic term does not significantly improve the fit of the model, which is again apparent from Fig. 3c.

Globally, 1 in 24 persons (1 in 19 men and 1 in 29 women) had the risk of developing CRC during their lifetime (before the age 85) whereas the risk of dying from CRC were 1 in 37 in males and 1 in 57 in females (Table 3; Table 4 of Appendix). There was wide geographical variations between the risk of developing and dying from CRC during lifetime i.e. before the age 85 (Table 3; Table 4 of Appendix). While the odds of CRC incidence were the greatest in Australia/New Zealand region with 1 in 13 persons (males 1 in 11; females: 1 in 15) were expected to develop CRC during their lifetime, the odds of CRC death, however, were the greatest in central and eastern Europe (both sexes 1 in 28; males 1 in 20; females 1 in 36). Country-wise, odds of developing CRC were the greatest in developed countries led by Hungary with odds of CRC incidence 1 in 10 (males 1 in 7; females 1 in 13). In females, the highest odds of CRC incidence and death were estimated in Singapore (incidence 1 in 11; death 1 in 27). Fifty-three countries had more than 5% risk of CRC incidence during a person’s lifetime, whereas 7 countries recorded greater than 10% risk of developing CRC. As per the development status, the CRC risk was the highest in developed countries and lowest in lesser developed and populous countries in Asia and Africa. India, for instance, had one of the lowest risks (incidence 1 in 120; death 1 in 149) of CRC incidence and mortality.

Table 3.

Region-wise probability of incidence and death due to colorectal cancer

	Incidence			Deaths
Population	Both	Male	Female	Both	Male	Female
Australia and New Zealand	7.83 (1 in 13)	8.98 (1 in 11)	6.75 (1 in 15)	2.77 (1 in 36)	3.16 (1 in 32)	2.4 (1 in 42)
Caribbean	3.97 (1 in 25)	4.01 (1 in 25)	3.94 (1 in 25)	2.37 (1 in 42)	2.45 (1 in 41)	2.29 (1 in 44)
Central America	2.17 (1 in 46)	2.38 (1 in 42)	1.98 (1 in 51)	1.17 (1 in 85)	1.3 (1 in 77)	1.06 (1 in 94)
Central and Eastern Europe	5.9 (1 in 17)	7.92 (1 in 13)	4.7 (1 in 21)	3.56 (1 in 28)	4.93 (1 in 20)	2.78 (1 in 36)
Eastern Africa	1.49 (1 in 67)	1.54 (1 in 65)	1.45 (1 in 69)	1.19 (1 in 84)	1.28 (1 in 78)	1.12 (1 in 89)
Eastern Asia	5.67 (1 in 18)	6.86 (1 in 15)	4.58 (1 in 22)	2.83 (1 in 35)	3.44 (1 in 29)	2.28 (1 in 44)
Melanesia	2.82 (1 in 35)	4.23 (1 in 24)	1.75 (1 in 57)	1.85 (1 in 54)	3.02 (1 in 33)	0.97 (1 in 103)
Micronesia	3.63 (1 in 28)	4.1 (1 in 24)	3.13 (1 in 32)	1.81 (1 in 55)	2.69 (1 in 37)	1.09 (1 in 92)
Middle Africa	1.72 (1 in 58)	1.84 (1 in 54)	1.63 (1 in 61)	1.47 (1 in 68)	1.61 (1 in 62)	1.37 (1 in 73)
North America	5.18 (1 in 19)	5.88 (1 in 17)	4.57 (1 in 22)	1.88 (1 in 53)	2.21 (1 in 45)	1.59 (1 in 63)
Northern Africa	1.68 (1 in 60)	1.9 (1 in 53)	1.51 (1 in 66)	1.14 (1 in 88)	1.35 (1 in 74)	0.97 (1 in 103)
Northern Europe	6.89 (1 in 15)	8.23 (1 in 12)	5.74 (1 in 17)	2.9 (1 in 34)	3.55 (1 in 28)	2.37 (1 in 42)
Polynesia	3.48 (1 in 29)	4.53 (1 in 22)	2.55 (1 in 39)	0.77 (1 in 130)	1.35 (1 in 74)	0.26 (1 in 385)
South America	3.91 (1 in 26)	4.42 (1 in 23)	3.51 (1 in 28)	2.14 (1 in 47)	2.53 (1 in 40)	1.84 (1 in 54)
South-Central Asia	0.93 (1 in 108)	1.2 (1 in 83)	0.68 (1 in 147)	0.72 (1 in 139)	0.95 (1 in 105)	0.5 (1 in 200)
South-Eastern Asia	2.92 (1 in 34)	3.65 (1 in 27)	2.35 (1 in 43)	1.84 (1 in 54)	2.36 (1 in 42)	1.46 (1 in 68)
Southern Africa	2.89 (1 in 35)	3.78 (1 in 26)	2.37 (1 in 42)	1.72 (1 in 58)	2.37 (1 in 42)	1.35 (1 in 74)
Southern Europe	6.64 (1 in 15)	8.66 (1 in 12)	4.95 (1 in 20)	2.89 (1 in 35)	3.92 (1 in 26)	2.06 (1 in 49)
Western Africa	1.15 (1 in 87)	1.24 (1 in 81)	1.07 (1 in 93)	0.9 (1 in 111)	0.99 (1 in 101)	0.82 (1 in 122)
Western Asia	3.38 (1 in 30)	4.15 (1 in 24)	2.75 (1 in 36)	2.05 (1 in 49)	2.5 (1 in 40)	1.69 (1 in 59)
Western Europe	6.12 (1 in 16)	7.48 (1 in 13)	4.94 (1 in 20)	2.6 (1 in 38)	3.32 (1 in 30)	1.99 (1 in 50)

Data source: cumulative risk of developing and dying from cancer (before age 85) were procured from GLOBOCAN 2018 and the odds were calculated using the CRC risk. Odds of developing and dying from CRC are presented inside parenthesis

Table 4.

Country-wise probability of incidence and death due to colorectal cancer

	Incidence			Deaths
Country	Both	Male	Female	Both	Male	Female
Afghanistan	0.68 (1 in 147)	0.77 (1 in 130)	0.59 (1 in 169)	0.62 (1 in 161)	0.69 (1 in 145)	0.55 (1 in 182)
Albania	1.49 (1 in 67)	1.73 (1 in 58)	1.27 (1 in 79)	0.84 (1 in 119)	1.02 (1 in 98)	0.66 (1 in 152)
Algeria	2.6 (1 in 38)	2.93 (1 in 34)	2.29 (1 in 44)	1.64 (1 in 61)	1.97 (1 in 51)	1.35 (1 in 74)
Angola	1.04 (1 in 96)	1.22 (1 in 82)	0.9 (1 in 111)	0.79 (1 in 127)	0.96 (1 in 104)	0.66 (1 in 152)
Argentina	5.11 (1 in 20)	6.69 (1 in 15)	3.98 (1 in 25)	3 (1 in 33)	4.09 (1 in 24)	2.25 (1 in 44)
Armenia	4.81 (1 in 21)	4.42 (1 in 23)	5.06 (1 in 20)	3.19 (1 in 31)	3.21 (1 in 31)	3.16 (1 in 32)
Australia	7.77 (1 in 13)	8.95 (1 in 11)	6.67 (1 in 15)	2.7 (1 in 37)	3.09 (1 in 32)	2.33 (1 in 43)
Austria	4.56 (1 in 22)	5.91 (1 in 17)	3.44 (1 in 29)	2.29 (1 in 44)	3.16 (1 in 32)	1.6 (1 in 63)
Azerbaijan	2.01 (1 in 50)	2.85 (1 in 35)	1.41 (1 in 71)	1.54 (1 in 65)	2.31 (1 in 43)	1 (1 in 100)
Bahamas	4.59 (1 in 22)	5.6 (1 in 18)	3.75 (1 in 27)	2.2 (1 in 45)	2.91 (1 in 34)	1.68 (1 in 60)
Bahrain	2.41 (1 in 41)	3.12 (1 in 32)	1.73 (1 in 58)	1.72 (1 in 58)	2.28 (1 in 44)	1.26 (1 in 79)
Bangladesh	0.68 (1 in 147)	0.76 (1 in 132)	0.61 (1 in 164)	0.58 (1 in 172)	0.66 (1 in 152)	0.49 (1 in 204)
Barbados	8.25 (1 in 12)	9.65 (1 in 10)	7 (1 in 14)	3.99 (1 in 25)	4.87 (1 in 21)	3.28 (1 in 30)
Belarus	6.4 (1 in 16)	8.77 (1 in 11)	5.17 (1 in 19)	3.48 (1 in 29)	4.57 (1 in 22)	2.95 (1 in 34)
Belgium	7.53 (1 in 13)	9.47 (1 in 11)	5.9 (1 in 17)	2.51 (1 in 40)	3.15 (1 in 32)	1.99 (1 in 50)
Belize	1.52 (1 in 66)	1.48 (1 in 68)	1.54 (1 in 65)	1.16 (1 in 86)	1.08 (1 in 93)	1.22 (1 in 82)
Benin	0.91 (1 in 110)	1.42 (1 in 70)	0.52 (1 in 192)	0.68 (1 in 147)	1.07 (1 in 93)	0.37 (1 in 270)
Bhutan	0.68 (1 in 147)	0.78 (1 in 128)	0.57 (1 in 175)	0.65 (1 in 154)	0.74 (1 in 135)	0.53 (1 in 189)
Bolivia	1.16 (1 in 86)	1.29 (1 in 78)	1.03 (1 in 97)	0.75 (1 in 133)	0.87 (1 in 115)	0.65 (1 in 154)
Bosnia and Herzegovina	5.19 (1 in 19)	6.61 (1 in 15)	4.07 (1 in 25)	3.19 (1 in 31)	4.34 (1 in 23)	2.33 (1 in 43)
Botswana	0.53 (1 in 189)	0.93 (1 in 108)	0.27 (1 in 370)	0.4 (1 in 250)	0.73 (1 in 137)	0.2 (1 in 500)
Brazil	4 (1 in 25)	4.42 (1 in 23)	3.68 (1 in 27)	2.09 (1 in 48)	2.43 (1 in 41)	1.85 (1 in 54)
Brunei	6.97 (1 in 14)	8.72 (1 in 11)	5.44 (1 in 18)	3.03 (1 in 33)	4.15 (1 in 24)	2.07 (1 in 48)
Bulgaria	5.67 (1 in 18)	7.82 (1 in 13)	4.1 (1 in 24)	3.47 (1 in 29)	5.05 (1 in 20)	2.36 (1 in 42)
Burkina Faso	1.21 (1 in 83)	1.05 (1 in 95)	1.32 (1 in 76)	1.11 (1 in 90)	0.98 (1 in 102)	1.18 (1 in 85)
Burundi	1.93 (1 in 52)	1.67 (1 in 60)	2.14 (1 in 47)	1.81 (1 in 55)	1.61 (1 in 62)	1.97 (1 in 51)
Cabo Verde	1.97 (1 in 51)	2.65 (1 in 38)	1.64 (1 in 61)	1.26 (1 in 79)	1.76 (1 in 57)	0.99 (1 in 101)
Cambodia	2.39 (1 in 42)	2.8 (1 in 36)	2.12 (1 in 47)	1.85 (1 in 54)	2.16 (1 in 46)	1.65 (1 in 61)
Cameroon	1.53 (1 in 65)	1.75 (1 in 57)	1.35 (1 in 74)	1.24 (1 in 81)	1.46 (1 in 68)	1.06 (1 in 94)
Canada	6.49 (1 in 15)	7.4 (1 in 14)	5.68 (1 in 18)	2.55 (1 in 39)	3.1 (1 in 32)	2.06 (1 in 49)
Central African Republic	1.19 (1 in 84)	1.43 (1 in 70)	1.01 (1 in 99)	1.16 (1 in 86)	1.41 (1 in 71)	0.98 (1 in 102)
Chad	1.07 (1 in 93)	1.23 (1 in 81)	0.93 (1 in 108)	0.97 (1 in 103)	1.11 (1 in 90)	0.85 (1 in 118)
Chile	4.65 (1 in 22)	5.45 (1 in 18)	4.03 (1 in 25)	2.62 (1 in 38)	3.11 (1 in 32)	2.25 (1 in 44)
China	5.05 (1 in 20)	5.99 (1 in 17)	4.16 (1 in 24)	2.86 (1 in 35)	3.42 (1 in 29)	2.34 (1 in 43)
Colombia	3.45 (1 in 29)	3.68 (1 in 27)	3.27 (1 in 31)	1.89 (1 in 53)	2.09 (1 in 48)	1.74 (1 in 57)
Comoros	1.01 (1 in 99)	0.83 (1 in 120)	1.14 (1 in 88)	1.01 (1 in 99)	0.83 (1 in 120)	1.14 (1 in 88)
Congo, Democratic Republic of	2.21 (1 in 45)	2.26 (1 in 44)	2.19 (1 in 46)	1.95 (1 in 51)	2.05 (1 in 49)	1.88 (1 in 53)
Congo, Republic of	1.14 (1 in 88)	1.35 (1 in 74)	0.97 (1 in 103)	0.9 (1 in 111)	1.08 (1 in 93)	0.75 (1 in 133)
Costa Rica	3.61 (1 in 28)	3.83 (1 in 26)	3.42 (1 in 29)	2.09 (1 in 48)	2.32 (1 in 43)	1.88 (1 in 53)
Côte d’Ivoire	1.11 (1 in 90)	0.91 (1 in 110)	1.35 (1 in 74)	0.95 (1 in 105)	0.79 (1 in 127)	1.13 (1 in 88)
Croatia	7.19 (1 in 14)	9.91 (1 in 10)	5.22 (1 in 19)	4.71 (1 in 21)	7 (1 in 14)	3.14 (1 in 32)
Cuba	4.12 (1 in 24)	3.74 (1 in 27)	4.45 (1 in 22)	2.76 (1 in 36)	2.66 (1 in 38)	2.85 (1 in 35)
Cyprus	5.39 (1 in 19)	7.81 (1 in 13)	3.28 (1 in 30)	2.62 (1 in 38)	3.81 (1 in 26)	1.62 (1 in 62)
Czechia	6.96 (1 in 14)	9.31 (1 in 11)	5.19 (1 in 19)	3.17 (1 in 32)	4.4 (1 in 23)	2.26 (1 in 44)
Denmark	8.99 (1 in 11)	10.29 (1 in 10)	7.85 (1 in 13)	3.18 (1 in 31)	3.71 (1 in 27)	2.74 (1 in 36)
Djibouti	0.81 (1 in 123)	1 (1 in 100)	0.65 (1 in 154)	0.75 (1 in 133)	0.97 (1 in 103)	0.56 (1 in 179)
Dominican Republic	2.66 (1 in 38)	2.62 (1 in 38)	2.68 (1 in 37)	1.64 (1 in 61)	1.66 (1 in 60)	1.62 (1 in 62)
Ecuador	2.53 (1 in 40)	2.37 (1 in 42)	2.66 (1 in 38)	1.45 (1 in 69)	1.44 (1 in 69)	1.46 (1 in 68)
Egypt	1.16 (1 in 86)	1.15 (1 in 87)	1.16 (1 in 86)	0.78 (1 in 128)	0.78 (1 in 128)	0.77 (1 in 130)
El Salvador	1.91 (1 in 52)	1.71 (1 in 58)	2.07 (1 in 48)	1.08 (1 in 93)	0.96 (1 in 104)	1.16 (1 in 86)
Equatorial Guinea	0.98 (1 in 102)	1.19 (1 in 84)	0.79 (1 in 127)	0.92 (1 in 109)	1.15 (1 in 87)	0.71 (1 in 141)
Eritrea	1.03 (1 in 97)	1.25 (1 in 80)	0.85 (1 in 118)	0.91 (1 in 110)	1.13 (1 in 88)	0.73 (1 in 137)
Estonia	6.64 (1 in 15)	8.18 (1 in 12)	5.8 (1 in 17)	3.36 (1 in 30)	4.87 (1 in 21)	2.55 (1 in 39)
Eswatini	0.59 (1 in 169)	0.77 (1 in 130)	0.49 (1 in 204)	0.46 (1 in 217)	0.67 (1 in 149)	0.34 (1 in 294)
Ethiopia	1.16 (1 in 86)	1.35 (1 in 74)	1.01 (1 in 99)	0.97 (1 in 103)	1.19 (1 in 84)	0.79 (1 in 127)
Fiji	1.87 (1 in 53)	2.02 (1 in 50)	1.77 (1 in 56)	1.2 (1 in 83)	1.5 (1 in 67)	0.99 (1 in 101)
Finland	5.38 (1 in 19)	6.45 (1 in 16)	4.5 (1 in 22)	2.18 (1 in 46)	2.79 (1 in 36)	1.69 (1 in 59)
France	6.39 (1 in 16)	7.92 (1 in 13)	5.08 (1 in 20)	2.55 (1 in 39)	3.31 (1 in 30)	1.91 (1 in 52)
France, Guadeloupe	3.92 (1 in 26)	4.59 (1 in 22)	3.4 (1 in 29)	2.32 (1 in 43)	3.53 (1 in 28)	1.39 (1 in 72)
France, La Réunion	5.3 (1 in 19)	6.31 (1 in 16)	4.45 (1 in 22)	2.4 (1 in 42)	2.95 (1 in 34)	1.94 (1 in 52)
France, Martinique	4.93 (1 in 20)	5.82 (1 in 17)	4.2 (1 in 24)	2.29 (1 in 44)	2.92 (1 in 34)	1.8 (1 in 56)
France, New Caledonia	5.36 (1 in 19)	6.51 (1 in 15)	4.28 (1 in 23)	1.64 (1 in 61)	2.06 (1 in 49)	1.24 (1 in 81)
French Guyana	3.8 (1 in 26)	4 (1 in 25)	3.45 (1 in 29)	0.84 (1 in 119)	1.37 (1 in 73)	0.39 (1 in 256)
French Polynesia	3.24 (1 in 31)	4.04 (1 in 25)	2.47 (1 in 40)	0.72 (1 in 139)	1.29 (1 in 78)	0.17 (1 in 588)
Gabon	0.75 (1 in 133)	0.94 (1 in 106)	0.6 (1 in 167)	0.5 (1 in 200)	0.64 (1 in 156)	0.41 (1 in 244)
Gaza Strip and West Bank	4.01 (1 in 25)	4.65 (1 in 22)	3.47 (1 in 29)	2.81 (1 in 36)	3.27 (1 in 31)	2.43 (1 in 41)
Georgia	1.85 (1 in 54)	2.42 (1 in 41)	1.49 (1 in 67)	1.26 (1 in 79)	1.71 (1 in 58)	0.98 (1 in 102)
Germany	5.62 (1 in 18)	6.74 (1 in 15)	4.65 (1 in 22)	2.56 (1 in 39)	3.27 (1 in 31)	1.96 (1 in 51)
Ghana	2.03 (1 in 49)	2.69 (1 in 37)	1.54 (1 in 65)	1.56 (1 in 64)	2.17 (1 in 46)	1.1 (1 in 91)
Greece	5.57 (1 in 18)	7.11 (1 in 14)	4.31 (1 in 23)	2.48 (1 in 40)	3.33 (1 in 30)	1.8 (1 in 56)
Guam	3.59 (1 in 28)	3.96 (1 in 25)	3.21 (1 in 31)	1.76 (1 in 57)	2.51 (1 in 40)	1.16 (1 in 86)
Guatemala	1.28 (1 in 78)	1.27 (1 in 79)	1.29 (1 in 78)	0.8 (1 in 125)	0.8 (1 in 125)	0.79 (1 in 127)
Guinea	0.31 (1 in 323)	0.33 (1 in 303)	0.29 (1 in 345)	0.28 (1 in 357)	0.3 (1 in 333)	0.26 (1 in 385)
Guinea-Bissau	1.29 (1 in 78)	1.53 (1 in 65)	1.11 (1 in 90)	1.23 (1 in 81)	1.52 (1 in 66)	1.01 (1 in 99)
Guyana	1.85 (1 in 54)	1.54 (1 in 65)	2.08 (1 in 48)	1.53 (1 in 65)	1.42 (1 in 70)	1.61 (1 in 62)
Haiti	2.93 (1 in 34)	3.29 (1 in 30)	2.7 (1 in 37)	2.07 (1 in 48)	2.06 (1 in 49)	2.1 (1 in 48)
Honduras	1.73 (1 in 58)	2.09 (1 in 48)	1.45 (1 in 69)	0.86 (1 in 116)	0.93 (1 in 108)	0.81 (1 in 123)
Hungary	10.09 (1 in 10)	14.02 (1 in 7)	7.43 (1 in 13)	5.01 (1 in 20)	7.37 (1 in 14)	3.53 (1 in 28)
Iceland	5.98 (1 in 17)	6.84 (1 in 15)	5.15 (1 in 19)	2.78 (1 in 36)	3.44 (1 in 29)	2.17 (1 in 46)
India	0.83 (1 in 120)	1.16 (1 in 86)	0.53 (1 in 189)	0.67 (1 in 149)	0.96 (1 in 104)	0.41 (1 in 244)
Indonesia	2.33 (1 in 43)	3.19 (1 in 31)	1.62 (1 in 62)	1.58 (1 in 63)	2.16 (1 in 46)	1.11 (1 in 90)
Iran, Islamic Republic of	2.6 (1 in 38)	2.99 (1 in 33)	2.18 (1 in 46)	1.37 (1 in 73)	1.52 (1 in 66)	1.19 (1 in 84)
Iraq	1.11 (1 in 90)	1.31 (1 in 76)	0.95 (1 in 105)	0.74 (1 in 135)	0.88 (1 in 114)	0.63 (1 in 159)
Ireland	7.55 (1 in 13)	9.5 (1 in 11)	5.77 (1 in 17)	3.21 (1 in 31)	3.95 (1 in 25)	2.56 (1 in 39)
Israel	4.32 (1 in 23)	5.3 (1 in 19)	3.54 (1 in 28)	2.4 (1 in 42)	2.89 (1 in 35)	2.01 (1 in 50)
Italy	6.45 (1 in 16)	7.95 (1 in 13)	5.18 (1 in 19)	2.61 (1 in 38)	3.36 (1 in 30)	2 (1 in 50)
Jamaica	5.14 (1 in 19)	4.4 (1 in 23)	5.78 (1 in 17)	2.63 (1 in 38)	2.28 (1 in 44)	2.93 (1 in 34)
Japan	8.09 (1 in 12)	10.27 (1 in 10)	6.17 (1 in 16)	2.92 (1 in 34)	3.72 (1 in 27)	2.24 (1 in 45)
Jordan	3.34 (1 in 30)	3.14 (1 in 32)	3.54 (1 in 28)	2.04 (1 in 49)	2.01 (1 in 50)	2.08 (1 in 48)
Kazakhstan	3.14 (1 in 32)	3.81 (1 in 26)	2.79 (1 in 36)	2.4 (1 in 42)	3.17 (1 in 32)	1.99 (1 in 50)
Kenya	1.68 (1 in 60)	1.95 (1 in 51)	1.47 (1 in 68)	1.21 (1 in 83)	1.48 (1 in 68)	0.99 (1 in 101)
Korea, Democratic Republic of	3.88 (1 in 26)	4.7 (1 in 21)	3.37 (1 in 30)	2.17 (1 in 46)	2.62 (1 in 38)	1.91 (1 in 52)
Korea, Republic of	8.38 (1 in 12)	11.25 (1 in 9)	5.97 (1 in 17)	2.23 (1 in 45)	3.06 (1 in 33)	1.61 (1 in 62)
Kuwait	2.98 (1 in 34)	3.05 (1 in 33)	2.94 (1 in 34)	1.91 (1 in 52)	1.98 (1 in 51)	1.86 (1 in 54)
Kyrgyzstan	1.58 (1 in 63)	1.61 (1 in 62)	1.52 (1 in 66)	1.31 (1 in 76)	1.41 (1 in 71)	1.22 (1 in 82)
Lao People’s Democratic Republic	2.72 (1 in 37)	2.99 (1 in 33)	2.51 (1 in 40)	1.97 (1 in 51)	2.23 (1 in 45)	1.78 (1 in 56)
Latvia	7.21 (1 in 14)	9.81 (1 in 10)	5.87 (1 in 17)	3.31 (1 in 30)	4.64 (1 in 22)	2.65 (1 in 38)
Lebanon	4.13 (1 in 24)	4.41 (1 in 23)	3.9 (1 in 26)	2.58 (1 in 39)	2.83 (1 in 35)	2.37 (1 in 42)
Lesotho	0.54 (1 in 185)	0.81 (1 in 123)	0.39 (1 in 256)	0.46 (1 in 217)	0.72 (1 in 139)	0.32 (1 in 313)
Liberia	0.73 (1 in 137)	0.63 (1 in 159)	0.82 (1 in 122)	0.68 (1 in 147)	0.6 (1 in 167)	0.74 (1 in 135)
Libya	2.21 (1 in 45)	2.49 (1 in 40)	1.99 (1 in 50)	1.58 (1 in 63)	1.85 (1 in 54)	1.37 (1 in 73)
Lithuania	5.77 (1 in 17)	7.93 (1 in 13)	4.57 (1 in 22)	3.2 (1 in 31)	5.04 (1 in 20)	2.2 (1 in 45)
Luxembourg	6.21 (1 in 16)	7.43 (1 in 13)	5.21 (1 in 19)	2.67 (1 in 37)	3.42 (1 in 29)	2.05 (1 in 49)
Madagascar	1.35 (1 in 74)	1.19 (1 in 84)	1.47 (1 in 68)	1.07 (1 in 93)	0.98 (1 in 102)	1.15 (1 in 87)
Malawi	0.53 (1 in 189)	0.64 (1 in 156)	0.47 (1 in 213)	0.43 (1 in 233)	0.54 (1 in 185)	0.35 (1 in 286)
Malaysia	4.3 (1 in 23)	4.78 (1 in 21)	3.86 (1 in 26)	2.87 (1 in 35)	3.25 (1 in 31)	2.51 (1 in 40)
Maldives	2.28 (1 in 44)	2.94 (1 in 34)	1.55 (1 in 65)	1.57 (1 in 64)	2.4 (1 in 42)	0.67 (1 in 149)
Mali	2.07 (1 in 48)	1.75 (1 in 57)	2.33 (1 in 43)	1.78 (1 in 56)	1.56 (1 in 64)	1.96 (1 in 51)
Malta	6.63 (1 in 15)	8.56 (1 in 12)	4.99 (1 in 20)	2.81 (1 in 36)	3.62 (1 in 28)	2.16 (1 in 46)
Mauritania	1.27 (1 in 79)	1.03 (1 in 97)	1.44 (1 in 69)	1.03 (1 in 97)	0.86 (1 in 116)	1.15 (1 in 87)
Mauritius	3.08 (1 in 32)	3.8 (1 in 26)	2.55 (1 in 39)	2.04 (1 in 49)	2.47 (1 in 40)	1.71 (1 in 58)
Mexico	2.16 (1 in 46)	2.41 (1 in 41)	1.93 (1 in 52)	1.14 (1 in 88)	1.3 (1 in 77)	1 (1 in 100)
Mongolia	1.29 (1 in 78)	1.36 (1 in 74)	1.25 (1 in 80)	0.72 (1 in 139)	0.83 (1 in 120)	0.65 (1 in 154)
Montenegro	3.55 (1 in 28)	4.13 (1 in 24)	3.05 (1 in 33)	2.17 (1 in 46)	2.63 (1 in 38)	1.83 (1 in 55)
Morocco	1.92 (1 in 52)	2.26 (1 in 44)	1.63 (1 in 61)	1.33 (1 in 75)	1.67 (1 in 60)	1.05 (1 in 95)
Mozambique	0.61 (1 in 164)	0.66 (1 in 152)	0.58 (1 in 172)	0.54 (1 in 185)	0.59 (1 in 169)	0.5 (1 in 200)
Myanmar	1.73 (1 in 58)	2.13 (1 in 47)	1.43 (1 in 70)	1.28 (1 in 78)	1.58 (1 in 63)	1.06 (1 in 94)
Namibia	1.25 (1 in 80)	1.48 (1 in 68)	1.09 (1 in 92)	0.8 (1 in 125)	1.04 (1 in 96)	0.64 (1 in 156)
Nepal	1.32 (1 in 76)	1.09 (1 in 92)	1.53 (1 in 65)	1.15 (1 in 87)	0.99 (1 in 101)	1.3 (1 in 77)
New Zealand	8.14 (1 in 12)	9.13 (1 in 11)	7.23 (1 in 14)	3.12 (1 in 32)	3.51 (1 in 28)	2.77 (1 in 36)
Nicaragua	2.28 (1 in 44)	1.99 (1 in 50)	2.51 (1 in 40)	1.47 (1 in 68)	1.29 (1 in 78)	1.6 (1 in 63)
Niger	0.88 (1 in 114)	0.91 (1 in 110)	0.84 (1 in 119)	0.86 (1 in 116)	0.9 (1 in 111)	0.81 (1 in 123)
Nigeria	0.95 (1 in 105)	1.08 (1 in 93)	0.84 (1 in 119)	0.67 (1 in 149)	0.78 (1 in 128)	0.57 (1 in 175)
Norway	9.45 (1 in 11)	10.5 (1 in 10)	8.52 (1 in 12)	3.46 (1 in 29)	4.06 (1 in 25)	2.93 (1 in 34)
Oman	1.87 (1 in 53)	1.91 (1 in 52)	1.78 (1 in 56)	1.25 (1 in 80)	1.26 (1 in 79)	1.22 (1 in 82)
Pakistan	0.68 (1 in 147)	0.73 (1 in 137)	0.63 (1 in 159)	0.57 (1 in 175)	0.62 (1 in 161)	0.52 (1 in 192)
Panama	3.45 (1 in 29)	4.09 (1 in 24)	2.89 (1 in 35)	1.78 (1 in 56)	2.08 (1 in 48)	1.51 (1 in 66)
Papua New Guinea	2.96 (1 in 34)	4.8 (1 in 21)	1.61 (1 in 62)	2.1 (1 in 48)	3.69 (1 in 27)	0.96 (1 in 104)
Paraguay	2.95 (1 in 34)	3.05 (1 in 33)	2.84 (1 in 35)	2 (1 in 50)	2.09 (1 in 48)	1.91 (1 in 52)
Peru	3.03 (1 in 33)	3.3 (1 in 30)	2.8 (1 in 36)	1.66 (1 in 60)	1.92 (1 in 52)	1.45 (1 in 69)
Philippines	4.06 (1 in 25)	5.14 (1 in 19)	3.25 (1 in 31)	2.83 (1 in 35)	3.59 (1 in 28)	2.28 (1 in 44)
Poland	6.4 (1 in 16)	8.85 (1 in 11)	4.68 (1 in 21)	3.93 (1 in 25)	5.64 (1 in 18)	2.79 (1 in 36)
Portugal	8.1 (1 in 12)	11.06 (1 in 9)	5.74 (1 in 17)	3.31 (1 in 30)	4.68 (1 in 21)	2.28 (1 in 44)
Puerto Rico	5.49 (1 in 18)	6.9 (1 in 14)	4.41 (1 in 23)	2.26 (1 in 44)	3.07 (1 in 33)	1.66 (1 in 60)
Qatar	3.41 (1 in 29)	3.7 (1 in 27)	2.96 (1 in 34)	2.55 (1 in 39)	2.69 (1 in 37)	2.38 (1 in 42)
Republic of Moldova	6.56 (1 in 15)	9.27 (1 in 11)	4.83 (1 in 21)	4.05 (1 in 25)	6.02 (1 in 17)	2.84 (1 in 35)
Romania	5.46 (1 in 18)	7.57 (1 in 13)	3.95 (1 in 25)	3.25 (1 in 31)	4.65 (1 in 22)	2.3 (1 in 43)
Russian Federation	5.51 (1 in 18)	7 (1 in 14)	4.72 (1 in 21)	3.48 (1 in 29)	4.63 (1 in 22)	2.9 (1 in 34)
Rwanda	3.29 (1 in 30)	3.15 (1 in 32)	3.41 (1 in 29)	2.68 (1 in 37)	2.7 (1 in 37)	2.68 (1 in 37)
Saint Lucia	3.53 (1 in 28)	4.19 (1 in 24)	3.04 (1 in 33)	2.25 (1 in 44)	2.93 (1 in 34)	1.72 (1 in 58)
Samoa	4.32 (1 in 23)	5.98 (1 in 17)	2.89 (1 in 35)	1.07 (1 in 93)	1.5 (1 in 67)	0.76 (1 in 132)
Sao Tome and Principe	0.88 (1 in 114)	1.33 (1 in 75)	0.55 (1 in 182)	0.57 (1 in 175)	0.96 (1 in 104)	0.28 (1 in 357)
Saudi Arabia	2.37 (1 in 42)	2.8 (1 in 36)	1.85 (1 in 54)	1.3 (1 in 77)	1.58 (1 in 63)	0.99 (1 in 101)
Senegal	1.38 (1 in 72)	1.42 (1 in 70)	1.35 (1 in 74)	1.12 (1 in 89)	1.22 (1 in 82)	1.05 (1 in 95)
Serbia	6.64 (1 in 15)	9.04 (1 in 11)	4.71 (1 in 21)	3.84 (1 in 26)	5.45 (1 in 18)	2.64 (1 in 38)
Sierra Leone	1.1 (1 in 91)	0.94 (1 in 106)	1.24 (1 in 81)	1.01 (1 in 99)	0.86 (1 in 116)	1.15 (1 in 87)
Singapore	8.88 (1 in 11)	8.9 (1 in 11)	8.72 (1 in 11)	4.4 (1 in 23)	5.11 (1 in 20)	3.77 (1 in 27)
Slovakia	9.01 (1 in 11)	12.73 (1 in 8)	6.44 (1 in 16)	5.11 (1 in 20)	7.6 (1 in 13)	3.57 (1 in 28)
Slovenia	8.49 (1 in 12)	12.32 (1 in 8)	5.28 (1 in 19)	3.23 (1 in 31)	4.47 (1 in 22)	2.28 (1 in 44)
Solomon Islands	1.23 (1 in 81)	1.43 (1 in 70)	1.03 (1 in 97)	1.06 (1 in 94)	1.28 (1 in 78)	0.84 (1 in 119)
Somalia	1.31 (1 in 76)	1.52 (1 in 66)	1.12 (1 in 89)	1.25 (1 in 80)	1.47 (1 in 68)	1.05 (1 in 95)
South Africa	3.12 (1 in 32)	4.09 (1 in 24)	2.55 (1 in 39)	1.84 (1 in 54)	2.55 (1 in 39)	1.44 (1 in 69)
South Sudan	1.35 (1 in 74)	1.49 (1 in 67)	1.24 (1 in 81)	1.23 (1 in 81)	1.37 (1 in 73)	1.1 (1 in 91)
Spain	7.06 (1 in 14)	9.74 (1 in 10)	4.82 (1 in 21)	3.01 (1 in 33)	4.33 (1 in 23)	1.96 (1 in 51)
Sri Lanka	0.93 (1 in 108)	1.08 (1 in 93)	0.82 (1 in 122)	0.68 (1 in 147)	0.82 (1 in 122)	0.57 (1 in 175)
Sudan	0.92 (1 in 109)	1.16 (1 in 86)	0.72 (1 in 139)	0.77 (1 in 130)	1.02 (1 in 98)	0.57 (1 in 175)
Suriname	3.89 (1 in 26)	4.88 (1 in 20)	3.18 (1 in 31)	2.87 (1 in 35)	3.39 (1 in 29)	2.46 (1 in 41)
Sweden	6.03 (1 in 17)	6.74 (1 in 15)	5.4 (1 in 19)	2.77 (1 in 36)	3.28 (1 in 30)	2.32 (1 in 43)
Switzerland	5.15 (1 in 19)	6.3 (1 in 16)	4.16 (1 in 24)	2.08 (1 in 48)	2.64 (1 in 38)	1.61 (1 in 62)
Syrian Arab Republic	2.87 (1 in 35)	2.97 (1 in 34)	2.8 (1 in 36)	2.11 (1 in 47)	2.24 (1 in 45)	2.02 (1 in 50)
Tajikistan	0.69 (1 in 145)	0.81 (1 in 123)	0.58 (1 in 172)	0.58 (1 in 172)	0.72 (1 in 139)	0.46 (1 in 217)
Tanzania	2.09 (1 in 48)	1.7 (1 in 59)	2.41 (1 in 41)	1.62 (1 in 62)	1.38 (1 in 72)	1.82 (1 in 55)
Thailand	3.2 (1 in 31)	3.71 (1 in 27)	2.8 (1 in 36)	1.74 (1 in 57)	2.07 (1 in 48)	1.48 (1 in 68)
The former Yugoslav Republic of Macedonia	5.33 (1 in 19)	5.98 (1 in 17)	4.81 (1 in 21)	2.93 (1 in 34)	3.37 (1 in 30)	2.59 (1 in 39)
The Netherlands	8.13 (1 in 12)	9.93 (1 in 10)	6.51 (1 in 15)	3.55 (1 in 28)	4.28 (1 in 23)	2.92 (1 in 34)
The Republic of the Gambia	0.15 (1 in 667)	0.21 (1 in 476)	0.1 (1 in 1000)	0.15 (1 in 667)	0.2 (1 in 500)	0.1 (1 in 1000)
Timor-Leste	1.88 (1 in 53)	1.86 (1 in 54)	1.88 (1 in 53)	1.53 (1 in 65)	1.52 (1 in 66)	1.52 (1 in 66)
Togo	1.43 (1 in 70)	1.38 (1 in 72)	1.46 (1 in 68)	1.19 (1 in 84)	1.19 (1 in 84)	1.19 (1 in 84)
Trinidad and Tobago	4.12 (1 in 24)	4.63 (1 in 22)	3.71 (1 in 27)	2.22 (1 in 45)	2.64 (1 in 38)	1.9 (1 in 53)
Tunisia	2.3 (1 in 43)	2.55 (1 in 39)	2.09 (1 in 48)	1.49 (1 in 67)	1.68 (1 in 60)	1.33 (1 in 75)
Turkey	4.27 (1 in 23)	5.64 (1 in 18)	3.21 (1 in 31)	2.43 (1 in 41)	3.16 (1 in 32)	1.88 (1 in 53)
Turkmenistan	1.29 (1 in 78)	1.45 (1 in 69)	1.18 (1 in 85)	0.69 (1 in 145)	0.84 (1 in 119)	0.58 (1 in 172)
Uganda	1.86 (1 in 54)	1.75 (1 in 57)	1.94 (1 in 52)	1.56 (1 in 64)	1.48 (1 in 68)	1.61 (1 in 62)
Ukraine	5.12 (1 in 20)	6.92 (1 in 14)	4.12 (1 in 24)	3.29 (1 in 30)	4.53 (1 in 22)	2.61 (1 in 38)
United Arab Emirates	2.93 (1 in 34)	3.3 (1 in 30)	2.25 (1 in 44)	1.72 (1 in 58)	1.85 (1 in 54)	1.51 (1 in 66)
UK	6.8 (1 in 15)	8.17 (1 in 12)	5.57 (1 in 18)	2.87 (1 in 35)	3.48 (1 in 29)	2.35 (1 in 43)
USA	5.01 (1 in 20)	5.68 (1 in 18)	4.44 (1 in 23)	1.79 (1 in 56)	2.1 (1 in 48)	1.53 (1 in 65)
Uruguay	7.54 (1 in 13)	9.54 (1 in 10)	6.1 (1 in 16)	3.73 (1 in 27)	4.91 (1 in 20)	2.94 (1 in 34)
Uzbekistan	1.22 (1 in 82)	1.21 (1 in 83)	1.22 (1 in 82)	0.75 (1 in 133)	1 (1 in 100)	0.55 (1 in 182)
Vanuatu	0.72 (1 in 139)	0.64 (1 in 156)	0.81 (1 in 123)	0.69 (1 in 145)	0.64 (1 in 156)	0.73 (1 in 137)
Venezuela, Bolivarian Republic of	2.85 (1 in 35)	3.02 (1 in 33)	2.69 (1 in 37)	1.66 (1 in 60)	1.84 (1 in 54)	1.5 (1 in 67)
Viet Nam	2.51 (1 in 40)	3.11 (1 in 32)	2.12 (1 in 47)	1.55 (1 in 65)	2 (1 in 50)	1.28 (1 in 78)
World	4.25 (1 in 24)	5.15 (1 in 19)	3.48 (1 in 29)	2.18 (1 in 46)	2.69 (1 in 37)	1.76 (1 in 57)
Yemen	1.86 (1 in 54)	2.01 (1 in 50)	1.74 (1 in 57)	1.55 (1 in 65)	1.67 (1 in 60)	1.44 (1 in 69)
Zambia	0.75 (1 in 133)	0.89 (1 in 112)	0.66 (1 in 152)	0.49 (1 in 204)	0.65 (1 in 154)	0.38 (1 in 263)
Zimbabwe	2.01 (1 in 50)	2.35 (1 in 43)	1.77 (1 in 56)	1.55 (1 in 65)	1.85 (1 in 54)	1.34 (1 in 75)

Data source: cumulative risk of developing and dying from cancer (before age 85) were procured from GLOBOCAN 2018 and the odds were calculated using the CRC risk. Odds of developing and dying from CRC are presented inside parenthesis.

Discussion

We examined the CRC burden using estimates of incidence and mortality from GLOBOCAN 2018 [11, 17] and examined its association with socioeconomic status measured using HDI. We found that CRC incidence increases with age and has more proclivity towards males than females. While all-age incidence and mortality were the highest in high HDI countries led by China (incidence 521,490 and deaths 247,563), the age-standardized rates were the highest in very high HDI countries led by Hungary (ASIR 51.2/100,000) and South Korea (44.5/100,000); ASMR too was the highest in Hungary (21.5/100,000) followed by Slovakia (20.4/100,000). Due to large population size, East Asia led the world regions in terms of all-age incidence and death counts, whereas ASIR and ASMR were the highest in developed regions, e.g., Northern Europe recorded ASIR of 32.1/100,000 and central and eastern Europe recorded ASMR of 15.2/100,000. Both ASIR and ASMR were lowest in south-central Asia at estimated at 4.9/100,000 and 3.6/100,000, respectively, in 2018. Higher incidence in developed societies has already been documented before [20] and is attributable to a greater percentage of the older population, dietary patterns, and availability of screening procedures [21]. Higher risk of males towards CRC has been documented before and can be possibly attributed to factors such as greater prevalence of risk factors such as alcohol and smoking in males [22–24]. The differences in mortality rates, however, also reflect the role of factors other than alcohol and smoking, though it requires more research to provide conclusive evidence.

Ninety percent of CRC incidence and 92% of CRC deaths occurred in 50-plus age group (Fig. 2). As age increases, adenomatous polyps grows slowly from adenoma to frank carcinoma; therefore, CRC deaths can be prevented by the detection and removal of adenomatous polyps through early screening. Although operational screening modalities differ in terms of convenience and cost, mainly two types of screening procedures are currently employed. First is stool based, e.g., fecal occult blood test (FOBT), Guaiac-based FOBT, and fecal immunochemical test (FIT); second involves structural examinations such as flexible sigmoidoscopy and colonoscopy. Colonoscopy is considered to be the gold standard of CRC screening and diagnosis; it has higher specificity and sensitivity than the stool-based methods, the colonoscopy, however, is quite resource-intensive in comparison with stool-based methods [7]. Although different methods vary in terms of efficiency and their implementation varies geographically, randomized control trials have demonstrated that screening methods have been quite effective in early detection of adenomas and colorectal carcinoma, thereby boosting the survival rates [25–29]. There are currently two approaches to screening: population-wide and opportunistic. The population-wide screening is quite prevalent in Western countries, the opportunistic screening, however, had limited success in boosting the take-up rates [30]. As per WHO country survey on cancer control policies, FOBT-based screening procedure was available at public primary level in 82/160 of the responding countries, whereas colonoscopy was present in 70/160 countries (Table 5 of Appendix). Even in those countries where these screening modalities were available, most of the countries belonged to high/very high HDI category. The US Preventive Services Task Force (USPSTF) recommends screening for CRC in the 50–75 age group; those with familial history and other high-risk population are recomended for screening at a comparatively younger age and higher frequency [7]. S A significant percentage of US citizens still had no access to screening in 2010 [31]. Moreover, heterogenous participation rates were observed in developed societies owing to differential socioeconomic status and level of education, thereby resulting in inequalities in the disease outcomes [32].

Table 5.

Country-wise availability of screening modalities

Population	FOBT	Colonoscopy
Afghanistan	0	0
Albania	0	0
Algeria	0	0
Angola	ND	ND
Argentina	1	1
Armenia	1	0
Australia	1	1
Austria	1	1
Azerbaijan	1	0
Bahamas	1	0
Bahrain	1	1
Bangladesh	0	0
Barbados	1	1
Belarus	ND	ND
Belgium	1	1
Belize	1	1
Benin	0	0
Bhutan	0	1
Bolivia	1	0
Bosnia and Herzegovina	ND	ND
Botswana	0	0
Brazil	1	1
Brunei	1	1
Bulgaria	1	1
Burkina Faso	0	1
Burundi	0	0
Cabo Verde	ND	ND
Cambodia	0	DK
Cameroon	1	0
Canada	1	1
Central African Republic	0	0
Chad	ND	ND
Chile	1	1
China	1	1
Colombia	1	1
Comoros	1	0
Congo	0	1
Costa Rica	1	1
Côte d’Ivoire	0	0
Croatia	1	1
Cuba	1	1
Cyprus	1	1
Czechia	1	1
Democratic Republic of Congo	ND	ND
Denmark	1	1
Djibouti	0	0
Dominican Republic	1	0
Ecuador	1	0
Egypt	1	0
El Salvador	0	0
Equatorial Guinea	0	0
Eritrea	0	0
Estonia	1	0
Eswatini	0	0
Ethiopia	ND	ND
Fiji	1	1
Finland	1	1
France	1	1
France, Guadeloupe
France, La Réunion
France, Martinique
France, New Caledonia
French Guyana
French Polynesia
Gabon	1	1
Gambia	0	0
Gaza Strip and West Bank
Georgia	0	0
Germany	1	1
Ghana	0	0
Greece	1	1
Guam
Guatemala	0	0
Guinea	0	0
Guinea-Bissau	0	0
Guyana	ND	ND
Haiti	ND	ND
Honduras	0	0
Hungary	0	0
Iceland	1	0
India	0	0
Indonesia	0	0
Iran	1	1
Iraq	0	0
Ireland	1	1
Israel	1	1
Italy	1	1
Jamaica	1	1
Japan	1	1
Jordan	1	0
Kazakhstan	1	1
Kenya	0	0
Kuwait	0	0
Kyrgyzstan	0	0
Lao PDR	DK	1
Latvia	1	1
Lebanon	0	0
Lesotho	0	0
Liberia	0	0
Libya	0	0
Lithuania	1	1
Luxembourg	1	1
Macedonia FYR	1	1
Madagascar	0	0
Malawi	0	0
Malaysia	0	1
Maldives	0	0
Mali	0	0
Malta	1	1
Mauritania	0	0
Mauritius	ND	ND
Mexico	DK	DK
Moldova	1	1
Mongolia	0	0
Montenegro	0	0
Morocco	0	1
Mozambique	0	0
Myanmar	0	0
Namibia	1	DK
Nepal	0	0
Netherlands	0	0
New Zealand	1	0
Nicaragua	1	1
Niger	0	0
Nigeria	0	0
North Korea	0	0
Norway	1	1
Oman	1	1
Pakistan	0	0
Panama	1	0
Papua New Guinea	1	0
Paraguay	0	0
Peru	0	0
Philippines	0	0
Poland	1	1
Portugal	1	1
Puerto Rico
Qatar	1	0
Romania	0	0
Russian Federation	1	1
Rwanda	0	0
Saint Lucia	1	1
Samoa	1	0
Sao Tome and Principe	0	0
Saudi Arabia	0	0
Senegal	0	1
Serbia	1	1
Sierra Leone	ND	ND
Singapore	1	1
Slovakia	1	1
Slovenia	1	1
Solomon Islands	0	0
Somalia	0	0
South Africa	ND	ND
South Korea	1	1
South Sudan	ND	ND
Spain	1	1
Sri Lanka	0	0
Sudan	0	0
Suriname	1	1
Sweden	1	1
Switzerland	1	1
Syrian Arab Republic	1	1
Tajikistan	NR	NR
Tanzania	ND	ND
Thailand	0	0
Timor-Leste	ND	ND
Togo	0	0
Trinidad and Tobago	1	1
Tunisia	0	0
Turkey	1	1
Turkmenistan	1	1
Uganda	0	0
Ukraine	0	0
United Arab Emirates	1	0
UK	1	0
USA	1	1
Uruguay	1	1
Uzbekistan	0	0
Vanuatu	0	0
Venezuela	1	1
Viet Nam	0	0
Yemen	0	0
Zambia	0	0
Zimbabwe	0	1

All the data is procured from WHO Cancer Country Profiles. The answer to the question on screening availability was coded as follows: generally available at the public primary healthcare level (1) and not generally available at the public primary health care level (0). Data was not available for the countries for which no entry is there in the table

DK do not know, ND county did not respond to WHO questionnaire, NR country responded to WHO survey but did not responded to particular question

The modifiable risk factors that are associated with elevated risk of CRC include alcohol [33], smoking [34], red meat [35], obesity [36, 37], and type 2 diabetes [38], whereas fruit and vegetable consumption [39, 40] and physical activity reduce the risk of CRC [41]. The nonmodifiable risk factors of CRC include aging, familial history, preoccurrence of polyps, and inflammatory bowel diseases such as Crohn’s disease and ulcerative colitis [21]. Inflammation has recently been found to be associated with increased incidence of CRC; accordingly, anti-inflammatory drugs like low-dose aspirin has been found to be effective in reducing the CRC incidence [42–44].2

We observed high CRC burden in Asian countries exemplified by high absolute incidence and mortality in China, Japan, India, and South Korea with these four countries accounting for 41.6% (768,755 of 1.85 million) of incident cases and 40.7% (358,325 of 880,792) of global deaths in 2018. Previous studies also reported an increased risk of colorectal carcinoma in Asian populations [3]. The increasing incidence of CRC in these countries is reflective of changing lifestyle and behavior as factors including lack of physical activity and dietary patterns have been shown to be positively associated with high incidence of colorectal neoplasia in developed countries [21, 46]. The first pillar of the PPPM approach advocates for the prevention of CRC via controlling risk factors, the vast majority of which are related to lifestyle [33–41]. Preventable nature of CRC makes it a likely target of PPPM approach to medicine. For targeted therapy and precision medicine envisaged by PPPM, diagnostic, prognostic, and therapeutic markers need to be developed and continually adopted in CRC medicine. Carcinoembryonic antigen (CEA), for instance, has been shown to be a promising prognostic biomarker for CRC [47] and preliminary research has identified few hormones to have prognostic and therapeutic marker properties for CRC, though more research is still needed to explore their full potential [48].

The mortality due to CRC reflects the strength of the healthcare system and infrastructure to prevent, diagnose, and treat the disease. The CRC mortality rates were in concordance with incidence rates with ASMR being the highest in Europe (e.g. Hungary (21.5 per 100,000) and Slovakia (20.4 per 100,000)). The lesser developed (low/medium HDI) countries have comparatively lower ASMR because of large population and relatively lower life expectancy, the survival rates (proxied by MIR), however, were lot higher in developed countries (high/very high HDI) as compared to the lesser developed ones. Statistically too, we found that better socioeconomic status of a country measured using HDI has had strong statistically significant negative effect on MIR (a proxy for 5-year survival rate). Low survival rates in lesser developed countries reflect screening prevalence as well as treatment modalities for CRC, which depend critically upon the stage at which malignancy gets detected. While adenomatous polyps or a low-grade tumor detected during screening can be removed by polypectomy, the late-stage tumor, however, can be treated using colectomy (partial or complete removal of colon) in conjunction with adjuvant (neo)chemotherapy and/or radiotherapy. Few of these treatment modalities such as surgery (even if cancer or polyps are detected early) are insufficiently present in less developed countries [49].

Limitations

The accuracy and validity of the estimates of CRC examined in this paper is crucially dependent upon data availability from cancer registries which is far from complete in many of the less developed countries led by Africa. Therefore, the estimates produced for few countries lacking cancer registry mostly reflect estimates from the neighboring countries [11, 17]. Moreover, for the countries lacking coverage and completeness, the GLOBOCAN estimates reported in this paper are expected to be downward biased. Second, the estimates presented in this paper were available only for 1 year (i.e., 2018) which could not be utilized to gauge the temporal patterns of the CRC burden. Third, we employed MIR as a proxy indicator of 5-year survival rate which is not an exact measure of survival rate. This indicator, however, can serve as a useful proxy for the survival rate of colorectal neoplasia in the absence of country-wise exact measure of survival rate.

Conclusion and expert recommendations

High burden of CRC was estimated in developed countries and was correlated positively with HDI and but is also substantially high in Asian countries. It shows that as countries are moving up in the development hierarchy, they are emulating Westernized lifestyle and dietary habits which have manifested in high CRC incidence in these countries. As the vast majority of risk factors are associated with lifestyle and diet, and screening programs are available, the CRC burden can be curtailed to attain the sustainable development goal (SDG 3) of ensuring a healthy and quality life.

Against the rising burden, it is also noteworhty that CRC deaths can be prevented via primary approaches (i.e., control of risk factors) and secondary prevention using cancer screening; both of these approaches are fundamental to the preventive, predictive, and personalized approach to medicine [8–10]. PPPM approach epitomizes the changing philosophy of healthcare from illness to health, from treatment to prevention and from one-size-fits-all to personalized medicine [50]. PPPM approach to medicine requires effective cancer control policies, aware citizens (at-risk population and patient), healthcare infrastructure, and availability and affordability of various technologies (omics technologies etc) to offer personalized medicine [51, 52]. The adoption of the PPPM approach to cancer management, however, is not easy in the context of developing and less-developed countries. This is because the PPPM approach is an integrated approach that combines advantages of individual bio/medical fields through a multi-professional collaboration [9]; such multi-professional collaboration along with multi-omics approach is quite a challenging and costly task for low-resource economies. Additionally, a large percentage of people in low-resource economies are still poor and lacks access to basic healthcare facilities let alone personalized medicine. Therefore, at the policy level, the following strategies must be adopted for cancer management and control in concordance with PPPM approach to disease managment and control. First, prevention must be adopted as the first-line attack on colorectal carcinoma. The major thrust of any policy intervention must be on providing cost-effective screening services and ensure their availability at the broadest possible level. Second, universal health coverage (UHC) can ensure access to basic health services (screening and treatment), which can later be upgraded to provide precision and personalized medicine. Third, through health literacy campaigns, various preventive approaches, behavioral risk factors, and screening programs must be popularized and made available to high-risk populations. Finally, new-age screening devices, omics technologies, and diagnostic and prognostic biomarker panels suiting the low-cost requirements need to be continuously developed and adopted.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

The research is conducted using data available in the public domain and does not include any human participants and/or animals.