Disease Mapping for Stomach Cancer in Libya Based on Besag York Mollié (BYM) Model

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1 DI:0.034/APJCP Dsease Mappng for Stomach Cancer n Lbya: Bayesan Study RESEARC ARTICLE Dsease Mappng for Stomach Cancer n Lbya Based on Besag York Mollé (BYM) Model Maryam Ahmed Salem Alhdr *, or Azah Samat, Zulkfley Mohamed Abstract Globally, Cancer s the ever-ncreasng health problem and most common cause of medcal deaths. In Lbya, t s an mportant health concern, especally n the settng of an agng populaton and lmted healthcare facltes. Therefore, the goal of ths research s to map of the county cancer ncdence rate usng the Bayesan method and dentfy the hgh-rsk regons (for the frst tme n a decade). In the feld of dsease mappng, very lttle has been done to address the ssue of analyzng sparse cancer dseases n Lbya. Standardzed Morbdty Rato or SMR s known as a tradtonal approach to measure the relatve rsk of the dsease, whch s the rato of observed and expected number of accounts n a regon that has the greatest uncertanty f the dsease s rare or small geographcal regon. Therefore, to solve some of SMR s problems, we used statstcal smoothng or Bayesan models to estmate the relatve rsk for stomach cancer ncdence n Lbya n 007 based on the BYM model. Ths research begns wth a short offer of the SMR and Bayesan model wth BYM model, whch we appled to stomach cancer ncdence n Lbya. We compared all of the results usng maps and tables. We found that BYM model s potentally benefcal, because t gves better relatve rsk estmates compared to SMR method. As well as, t has can overcome the classcal method problem when there s no observed stomach cancer n a regon. Keywords: BYM model- standardzed morbdty rato- dsease mappng- relatve rsk- stomach cancer- Lbya Asan Pac J Cancer Prev, 8 (6), Introducton Cancer s an mportant publc health problem worldwde. Cancer dsease mpacts everyone regardless of age, gender and class. There are several rsk factors that cause cancer whch are alcohol use, physcal nactvty, tobacco use and unhealthy det are the man cancer rsk factors, as well as some chronc nfectons, whch have man relevance n low- and mddle-ncome countres, ncludng, Lbya. In Lbya, cancer s the thrd leadng cause of death after car accdent and cardovascular dsease, therefore cancer s an mportant problem n publc health n Lbya, partcularly n the settng of an agng populaton and lmted healthcare facltes. For nstance, stomach cancer has the hghest prevalence of dsease dgestve cancer n Lbya especally West and orth dstrcts of Lbya (Alhdr et al., 06; Bodalal and Bendardaf, 04; Bodalal et al., 04). Medcally, stomach cancer known as gastrc cancer and t s a cancer that starts n the stomach. As wth other cancers, the cause of stomach cancer s not known wth certanty, but always assocated wth peptc ulcers, nflammaton of the stomach s accompaned by shrnkng the stomach. A stomach cancer rsk factor s any type of factor that ncreases the rsk of developng stomach cancer. Many of the most mportant rsk factors for stomach cancer are beyond the control, such as age, famly hstory, and medcal hstory. Although t s uncertan what the cause of gastrc cancer, however, factors that may ncrease the rsk of stomach cancer are: Consumpton of salted and smoked foods Rarely consume fruts and vegetables A famly medcal hstory of gastrc cancer n whch there Infectons caused by elcobacter pylor, a bacterum lvng n the mucous lnng of the stomach Chronc gastrc nflammaton, whch refers to a long-term stomach nflammaton. Perncous anaema, whch s a decrease n the number of red blood cells that occurs when the dgestve tract cannot absorb vtamn B properly. Smokng In recent years, a number of studes have been conducted to map the geographcal spread of stomach cancer ncdence, such as a study done by Mohebb and hs colleagues (008; 0) usng adjusted age-specfc standardzed ncdence rato (SIR) n the southwest of the Department of Statstcs, Faculty of Scence, Unversty of Trpol, Alfernag, Trpol, Lbya, Department of Mathematcs, Faculty of Scence and Mathematcs, Unverst Penddkan Sultan Idrs, Tanjong Malm, Perak, Malaysa. *For Correspondence: M.alhdr@uot.edu.ly, m.alhdr@yahoo.com Asan Pacfc Journal of Cancer Preventon, Vol 8 479

2 Maryam Ahmed Alhdr et al Caspan Sea from 00 to 005. In addton, the prevous studes have consdered countes of orthern provnces of Iran as clustered and has hgh-rsk ncdence rate cluster of stomach cancer (Mohebb et al., 008; 0). In Lbya, studes on geographcal analyss for cancer n the country at all s poor. Ths s because only the Eastern part of the country were consdered. Accordng to Abdel-aser et al., (0) ths s due to stomach cancer wth elcobacter pylor nfecton n promnent n Eastern Lbya durng the perod from 000 to 00. El-Mstr et al., (006) and Elzouk and Alkhoms (005) showed that stomach cancer s the second most prevalent dsease n Benghaz (the largest dstrct n eastern Lbya) after colorectal cancer. The age-standardzed rates of stomach cancer n the Benghaz cancer regstry were.6 new cases per 00,000 men-years and 8.8 per 00,000 women-years, respectvely (Elzouk and Alkhoms, 005). o such publshed works or studes were constructed to study or determne the pattern geographcal dstrbutons of stomach cancer n Lbya at all. Therefore, the goal of ths research s to characterze some geographcal features that assocated wth stomach cancer n Lbya. To the best of our nsght, such results on Lbyan database have not been dstrbuted or publshed already (for the frst tme n a decade). In other words, the man am of ths study s to dscuss and compare the relatve rsk estmaton for stomach cancer dsease mappng based on two dfferent approaches. These nvolve the analyss for relatve rsk estmaton based on the SMR method BYM and, the applcaton of these methods to observed stomach cancer data from Lbya to descrbe geographc of dsease rsk and dentfyng unusual hgh and low rsk areas. The areas or regons of Lbya vary n sze, shape and populaton sze (Fgure ). In ths study, we dscuss and demonstrate the most common methods used n the study of dsease mappng, whch s the classcal method that known as Standardzed Morbdty Rato and BYM model. We wll focus on ts applcaton to stomach cancer data n Lbya. Ths study s organzed as follows. Frst, n Secton, we revew and descrbe the classcal method n estmatng relatve rsk usng SMR method. Ths ncludes the defnton of SMR and ts drawbacks. Then we move to descrbe and overvew of the common applcaton of Bayesan methodology, that called as BYM model whch s appled and used by Lawson et al., (003), wll be n next secton. Secton 3 descrbes the cancer data used n our applcaton and presented fndngs. As well as several results presented n ths secton based on these two methods, whch are appled to observed stomach cancer data n Lbya n order to demonstrate and dentfy a better method of estmatng stomach rsk. Fnally, we close wth some dscusson n Secton 4. Materals and Methods Standardzed Mortalty Rato (SMR) Method In dsease mappng, SMR s the common statstcs used n spatal studes. The man am of the SMR s to estmate the RR of a certan dsease n a certan map, whch may be nterpreted as the probablty that a person 480 Asan Pacfc Journal of Cancer Preventon, Vol 8 wthn a specfed regon contracts the dsease dvded by the probablty that a person n the populaton contracts the dsease. In the feld of epdemology studes, SMR represents ether standardzed mortalty rato or the standardzed morbdty rato, when mortalty refers to death whle morbdty refers to the ncdence. owever, n general notaton, suppose that, where,,.., ( ndexes the areas or regons), ndcates the observed cases of a certan dsease of the study, and let E represents the expected cases or expected number of cases. Usng these values as obtaned from the avalable data, we can calculate the relatve rsk θ for area, whch s the SMR defned as S MR θˆ ˆ () E For the expected value E, t could be calculated by usng a partcular formula as below: E ˆ, then θ Where the s the populaton of dstrct/area. ere standardzaton s completed by the total populaton at rsk, assumng everybody s equal at rsk. Consequently, we estmate the relatve rsk usng formula: SMR ˆ θˆ ( ) whch s defned to be the probablty that a person wthn the dstrct/area contracts the dsease dvded by the probablty that a person n the populaton contracts the dsease. Samat and Percy (008) used the Equaton () for the SMR n ther study and appled t to dengue dsease mappng n Malaysa. Accordng to Lawson et al., (003), although SMR s used commonly as measure to estmate the true relatve rsk, but at the same tme, t has some problems assocated wth the use of t. SMR s based on a rato estmator, the mean and varance (SMR, SMR /E ) of SMR are very hghly dependent on expected count E. Furthermore, f there are areas wth no observed count data, mathematcally the SMR s necessarly zero. Meza (003), showed that ths problem of SMR makes the nterpretaton of SMR dffcult and t should be done wth cauton and also ponts out other problems of usng SMR, whch s that the SMR s a relable measure of relatve rsk for large geographcal regons such as countres or states, but s unrelable for small areas such as countes. owever, to be able to overcome these problems of usng of SMR method, many researchers have produce other alternatve methods to estmate the relatve rsk of the dsease. ne of these methods was the use of Bayesan methods. In ths research, we suggested very common method to estmate the relatve rsk of a dsease, as wll be dscussed n next secton.

3 Besag York Mollé (BYM) Model To address the problem of SMRs, n ths research the BYM model wll be used to analyss the data, as well as to consder the nformaton of the adjacent neghbours of each dstrct (area). The man dea for ths model s to produce a more relable estmaton for relatve rsks and for small areas or rare dsease. Ths s by borrowng requred nformaton from the neghbourng areas. In ths model, the relatve rsk s modelled wth addtonal consderaton. Area-specfc random effects whch are dvded nto two components. The frst component s u that takes nto account the effects that vary n a structured manner n space (clusterng or correlated heterogenety). The second component s v that takes nto account the effects that vary n an unstructured way between areas (uncorrelated heterogenety). Therefore, the model ntroduced by Clayton and Kaldor (987) and developed by Besag et al., (99), s formulated as follows: ( E θ ), Log( θ ) α + u v ~ Posson + where θ exp( α +u + v ), α s an ntercept (an overall level of the relatve rsk) and E and θ be the observed count, expected count and relatve rsk parameter n the th area respectvely, u s the correlated heterogenety and v s the uncorrelated heterogenety. The uncorrelated heterogenetes are assumed to follow a normal dstrbuton, as follows: v ~ (0, τ ) v For the frst component, whch s the clusterng component, a spatal correlaton structure s used, where estmaton of the rsk n any area depends on neghbourng areas. The condtonal autoregressve (CAR) model proposed by Besag et al. (99) wll be used to model the dstrbuton of the correlated heterogenety as: [ u u j j / u kj uj k k, k, τ ]~ ( u, τ ) where: k u ωk, τ j ω τ f u ; ωk ωk 0 f k j j, k, are adjectent (), k, are not adjectent DI:0.034/APJCP Dsease Mappng for Stomach Cancer n Lbya: Bayesan Study estmaton for stomach cancer dsease mappng n Lbya. Cancer Data In ths appled, ecologcal research, nformaton of the Lbyan dstrcts for one year 007 was analyzed, whch s obtaned from Afrca ncology Insttute (AI) (Sabratha Cancer Regstry, 008; Mnstry of ealth, 0). These admnstratve dstrcts are Alnkat, Zawa, Aljafara, Trpol, Almergab, Musrata, Srt, Benghaz, Almarg, Aljabal Alakhader, Darna, Albatnan, alut, Aljabal Algarb, Wad Shatee, Aljufra, Ejdabya, Ghat, Wad Alhya, Sabha, Morzuk and Alkufra. A geographcal system of Lbya s dstrcts s explaned n Fgure, where ID, name and populaton for each dstrct n the map are shown. Stomach cancer dsease data s used to llustrate the SMR model and BYM model to estmate the relatve rsk of dsease. The outcomes for the relatve rsk estmaton usng the BYM mode and the SMR for 007 are dsplayed n Table. Table presents two obvous dfferences n terms of the value of relatve rsk. Eleven dstrcts have value of relatve rsk equal to zero, n the absence of cases of observed stomach cancer based on analyss usng the SMR method. These dstrcts are Musrata, Benghaz, Almarg, Aljabal Alakhader, Darna, Albatnan, Ejdabya, Ghat, Wad Alhya, Sabha and Alkufra. Based on SMR method, susceptble people wthn the dstrct of alut have the hghest rsk of contractng stomach cancer, whle susceptble people wthn the above dstrcts have the lowest rsk of stomach cancer when compared wth people n the overall populaton. The correspondng values of relatve rsk are approxmately 4.935and 0, respectvely. Conversely, by usng BYM model, the fndng shows opposte results where the value of relatve rsk s not zero although there are dstrcts wth no observed counts of stomach cancer cases, whch can be a dsadvantage of the SMR approach. owever, the BYM model does not suffer from ths drawback and generates postve estmates of relatve rsk n dstrcts that have no observed case. In addton, from Table, Alnkat and Wad Shatee have a hgh value of relatve rsk durng 007. Estmaton For the parameters, n ths case are τ u and τ v, must be specfed. These parameters control the varablty of u and v. From ths source, u and v are consdered to have Gamma dstrbuton. Results Relatve Rsk f Dsease Usng SMR Method And BYM Model To Stomach Cancer Mappng Ths secton explans and dsplays the outcome of the applcatons of exstng relatve rsk estmaton methods, correspondng to the classcal model based on the standardzed morbdty rato and one of earlest examples of Bayesan mappng methods based on the BYM model usng observed stomach cancer n Lbya. Models were ftted to data usng WnBUGS software. Then, all of these outcomes are compared and dsplayed n the table and maps, to reveal the best-ftted model for relatve rsk Fgure. ames of Geographc Boundares, Code on the Map and Populaton of All Dstrcts n Lbya (Source: Alhdr et al., 06) Asan Pacfc Journal of Cancer Preventon, Vol 8 48

4 Maryam Ahmed Alhdr et al Table. Comparson between the Classcal Method and Smoothed Relatve Rsk Estmates Based on BYM Model and Ther Assocated Standard Devatons of Stomach Cancer Dsease for the Year 007 o. Dstrct E Relatve Rsk based on SMR Method Relatve Rsk based on BYM model RR SD RR SD Alnkat Zawa Aljafara Trpol Almergab Musrata Srt Benghaz Almarg Aljabal Alakhader Darna Albatnan alut Aljabal Algarb Wad Shatee Aljufra Ejdabya Ghat Wad Alhya Sabha Morzuk Alkufra RR: Relatve Rsk; SD: standard devaton; values hghlghted n bold: hghest or lowest relatve rsk or expected cases. usng the BYM model shows that susceptble people wthn the dstrct of Alnkat have the hghest rsk of about.504, whle susceptble people wthn the dstrcts of Musrata have the lowest rsk of about In addton, the results n Table dsplayed that a small populaton (small number of people n the th dstrct) has low expected counts, but SMR and standard error are hgh (see 8th dstrct, Ghat). Conversely, dstrct wth hgh populaton (hgh number of people n the th dstrct) has hgh expected counts, however SMR and standard error are low (see 4th dstrct, Trpol). Generally, SMRs have the greatest uncertanty because they have small populaton but standard error are hgh. So, we can say that the relatve rsks based on BYM provde a more stable rsk estmate such as yeldng low standard error than usng the classcal method. Fgure shows the relatonshp between the relatve rsk and standard error based on SMR method and BYM model. From ths Fgure A, t can be seen clear that the relatve rsk ncreases as standard error ncreases. Whle n Fgure B shows that the relatve rsk of dsease usng BYM model produced hgher precson of estmate than classcal method, because they have smaller standard error. Dsease Maps of Relatve Rsk Estmates for Stomach Cancer n Lbya Dsease maps are used to represent the dfferent levels of rsk for stomach cancer, whch covered all dstrcts n Lbya. Dseases maps graphcally dsplay statstcal outcomes for relatve rsk estmaton and are an nferental and fundamental decson-makng tool. In ths Fgure. A) Relatve Rsk Based on SMR Method vs Standard Error, B) Relatve Rsk Based on BYM Model vs Standard Error 48 Asan Pacfc Journal of Cancer Preventon, Vol 8 Fgure 3. Dseas Maps of Estmated Relatve Rsk Baed on A) SMR Method and B) BYM Model

5 study, multple colors are appled n the maps to dentfy and dsplay among the hot areas whch have hgh or low rsk of stomach cancer ncdents for all dstrcts n Lbya. The results represent the hot ponts of stomach cancer ncdents. Fgure 3 shows the rsk maps for stomach cancer based on the SMR method and the BYM model. Mappng ssues related to aggregated data are dscussed by Lawson (006), as well as nterpretaton and representaton ssues for dsease rsk n maps n other works (Pckle et al., 999; Lewandowsky et al., 993; Mungole et al., 999). To explan the results more effectvely, multple colors are used n the maps to hghlght areas of hgh-low rsks dstrcts of stomach cancer occurrences. In other words, n our applcaton, for the purposes of results explanaton, multple colors are used n the maps n order to dsplay and dentfy between the areas wth hgh and low rsk of stomach cancer occurrences for each dstrct n Lbya. Many studes pont out that there s no defntve way of choosng the levels of rsk, therefore t s farly arbtrary (McGrory and Ttterngton, 008). Therefore, each dstrct wll be categores nto fve dfferent levels of hazard. These levels are very hgh, hgh, medum, low and very low wth ther ntervals of (<0.5), (0.5,), (,.5), (.5,) and [(, )] respectvely. In our applcaton, dependng on the concept, and defnton of relatve rsk that s gven n several studes, we choose these ntervals to cover the range of observed values. In addton, the dark shade n the map ndcate the hghest rsk (very hgh) and by the lghtest shade ndcate the very lowest rsk (very low). Fgure 3A for the SMR map shows that there are sx dstrcts wth very hgh rsk of stomach cancer, whch are Alnkat, Zawa, alut, Wad Shatee, Aljufra, Ejdabya and Morzuk. Ths s followed by only one dstrct whch have hgh rsk, whch was Srt. Smlarly, only one dstrct has medum rsk, whch was n Aljafara. The dstrcts of Trpol, Almergab and Aljabal Algarb wth low rsk and the dstrcts of Musrata, Benghaz, Almarg, Aljaba Alakhader, Darna, Albatnan, Ejdabya, Ghat, Wad Alhya, Sabha and Alkufra have very low rsk. The BYM model map n Fgure 3B shows that the dstrct of Alnkat has hgh rsk of stomach cancer occurrences, whle no dstrcts have very hgh rsk. The dstrcts of medum rsk are Zawa, Aljafara, Srt, alut, Wad Shatee, Aljufra and Morzuk. whle the other fourteen dstrcts wth low rsk, nclude the dstrcts of Trpol, Almergab, Musrata, Benghaz, Almarg, Aljabal Alakhader, Darna, Albatnan, Aljabal Algarb, Ejdabya, Ghat, Wad Alhya, Sabha and Alkufra. Clearly, there are no dstrcts have very low rsk. Comparsons between the SMR method and BYM model for only one year 007 show some evdent dfferences n terms of the estmated rsks based on both maps consdered. Therefore, dsease maps are mostly meant to be a better presentaton tool for dentfyng areas, whch have very hgh, or hgh rsk of stomach cancer dsease, so that further nterest could be provded to these prorty dstrcts. Dscusson Bayesan dsease mappng technques wth BYM DI:0.034/APJCP Dsease Mappng for Stomach Cancer n Lbya: Bayesan Study model gves smoother relatve rsk, especally when rare dseases are nvestgated n an area whch has a small populaton. The fndngs based on BYM model offered better estmates of relatve rsk compared to the SMR method. These fndng showed that the BYM model can overcome the drawback of SMR especally when there s no observed stomach cancer case n certan dstrcts. The maps show that the hgh rsks are concentrated n the north-west part of the study area (the country) and least n the South and East. It s dentcal n terms of populaton concentraton congeston n the north and the least concentraton of populaton n the South and East. The dstrcts wth the hghest rsks are located n the west probably due to ol nstallatons n ths area such as Melltah l and Gas B.V, the Zawa l Refnng Company and Bour l Feld, as well as the electrcal power statons (Alsaker, 03). The hgh rsk of a specfc regon, the more focus s needed by the government and fnancal support are requred. Susceptble people wthn dstrcts located n the eastern part of the country have the lowest rsk based on both methods when compared to the people n the overall populaton. Acknowledgements The authors would lke to thank the staff members of the Afrcan ncology Insttute (AI) Sabratha at the Lbyan Cancer Centre and the staff n the Unverst Penddkan Sultan Idrs, Malaysa, for ther contnued help and support to complete ths research. Ths study has been extracted from PhD thess n Appled Statstcs at Mathematcs Department at Faculty of Scence and Mathematcs, Unverst Penddkan Sultan Idrs, Malaysa. References Alhdr MA, Samat A, Mohamed Z (06). 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