A simplified, combined protocol versus standard treatment for acute malnutrition in children 6–59 months (ComPAS trial): A cluster-randomized controlled non-inferiority trial in Kenya and South Sudan
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Jeanette Bailey aff001; Charles Opondo aff003; Natasha Lelijveld aff004; Bethany Marron aff001; Pamela Onyo aff005; Eunice N. Musyoki aff006; Susan W. Adongo aff006; Mark Manary aff007; André Briend aff008; Marko Kerac aff002
Působiště autorů:
International Rescue Committee, New York, New York, United States of America
aff001; Department of Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
aff002; Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, United Kingdom
aff003; No Wasted Lives, Action Against Hunger UK, London, United Kingdom
aff004; Action Against Hunger, Juba, South Sudan
aff005; International Rescue Committee, Nairobi, Kenya
aff006; Department of Pediatrics, Washington University School of Medicine, Saint Louis, Missouri, United States of America
aff007; Department of International Health, University of Tampere, Tampere, Finland
aff008; Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark
aff009; Centre for Maternal, Adolescent, Reproductive, & Child Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
aff010
Vyšlo v časopise:
A simplified, combined protocol versus standard treatment for acute malnutrition in children 6–59 months (ComPAS trial): A cluster-randomized controlled non-inferiority trial in Kenya and South Sudan. PLoS Med 17(7): e32767. doi:10.1371/journal.pmed.1003192
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pmed.1003192
Souhrn
Background
Malnutrition underlies 3 million child deaths worldwide. Current treatments differentiate severe acute malnutrition (SAM) from moderate acute malnutrition (MAM) with different products and programs. This differentiation is complex and costly. The Combined Protocol for Acute Malnutrition Study (ComPAS) assessed the effectiveness of a simplified, unified SAM/MAM protocol for children aged 6–59 months. Eliminating the need for separate products and protocols could improve the impact of programs by treating children more easily and cost-effectively, reaching more children globally.
Methods and findings
A cluster-randomized non-inferiority trial compared a combined protocol against standard care in Kenya and South Sudan. Randomization was stratified by country. Combined protocol clinics treated children using 2 sachets of ready-to-use therapeutic food (RUTF) per day for those with mid-upper arm circumference (MUAC) < 11.5 cm and/or edema, and 1 sachet of RUTF per day for those with MUAC 11.5 to <12.5 cm. Standard care clinics treated SAM with weight-based RUTF rations, and MAM with ready-to-use supplementary food (RUSF). The primary outcome was nutritional recovery. Secondary outcomes included cost-effectiveness, coverage, defaulting, death, length of stay, and average daily weight and MUAC gains. Main analyses were per-protocol, with intention-to-treat analyses also conducted. The non-inferiority margin was 10%. From 8 May 2017 to 31 March 2018, 2,071 children were enrolled in 12 combined protocol clinics (mean age 17.4 months, 41% male), and 2,039 in 12 standard care clinics (mean age 16.7 months, 41% male). In total, 1,286 (62.1%) and 1,202 (59.0%), respectively, completed treatment; 981 (76.3%) on the combined protocol and 884 (73.5%) on the standard protocol recovered, yielding a risk difference of 0.03 (95% CI −0.05 to 0.10, p = 0.52; per-protocol analysis, adjusted for country, age, and sex). The amount of ready-to-use food (RUTF or RUSF) required for a child with SAM to reach full recovery was less in the combined protocol (122 versus 193 sachets), and the combined protocol cost US$123 less per child recovered (US$918 versus US$1,041). There were 23 (1.8%) deaths in the combined protocol arm and 21 (1.8%) deaths in the standard protocol arm (adjusted risk difference 95% CI −0.01 to 0.01, p = 0.87). There was no evidence of a difference between the protocols for any of the other secondary outcomes. Study limitations included contextual factors leading to defaulting, a combined multi-country power estimate, and operational constraints.
Conclusions
Combined treatment for SAM and MAM is non-inferior to standard care. Further research should focus on operational implications, cost-effectiveness, and context (Asia versus Africa; emergency versus food-secure settings). This trial is complete and registered at ISRCTN (ISRCTN30393230).
Trial registration
The trial is registered at ISRCTN, trial number ISRCTN30393230.
Klíčová slova:
Cost-effectiveness analysis – Edema – Children – Kenya – Malnutrition – Nutrition – Weight gain – South Sudan
Zdroje
1. Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet. 2013;382:427–51. doi: 10.1016/S0140-6736(13)60937-X 23746772
2. United Nations Children’s Fund, World Health Organization, World Bank Group. Levels and trends in child malnutrition: UNICEF/WHO/World Bank Group joint child malnutrition estimates—key findings of the 2018 edition. Geneva: World Health Organization; 2018.
3. Bhutta ZA, Berkley JA, Bandsma RHJ, Kerac M, Trehan I, Briend A. Severe childhood malnutrition. Nat Rev Dis Primers. 2017;3:17067. doi: 10.1038/nrdp.2017.67 28933421
4. Collins S, Dent N, Binns P, Bahwere P, Sadler K, Hallam A. Management of severe acute malnutrition in children. Lancet. 2006;368(9551):1992–2000. doi: 10.1016/S0140-6736(06)69443-9 17141707
5. Lelijveld N, Seal A, Wells JC, Kirkby J, Opondo C, Chimwezi E, et al. Chronic disease outcomes after severe acute malnutrition in Malawian children (ChroSAM): a cohort study. Lancet Glob Health. 2016;4:e654–62. doi: 10.1016/S2214-109X(16)30133-4 27470174
6. Sustainable Development Solutions Network. Indicators and a monitoring framework: launching a data revolution for the Sustainable Development Goals. Paris: Sustainable Development Solutions Network; 2019 [cited 2019 Apr 2]. Available from: http://indicators.report/targets/2-2/.
7. Council of Research and Technical Advice on Acute Malnutrition. A Research agenda for acute malnutrition. London: No Wasted Lives Coalition; 2018 [cited2020 Jun 17]. Available from: https://www.nowastedlives.org/s/NoWastedLives_Research_Agenda_2018_English.pdf.
8. World Health Organization, Office of the United Nations High Commissioner for Refugees, United Nations Children’s Fund, World Food Programme. Simplified approaches for the treatment of child wasting. Geneva: World Health Organization; 2019 Mar [cited 2019 Apr 2]. Available from: https://www.who.int/nutrition/events/2019-consultation-simplified-treatment-childwasting-26to27march/en/.
9. Eleanor Crook Foundation. Minding the undernutrition evidence gap: findings of the key expert consultation. Eleanor Crook Foundation; 2018 October [cited 2020 Jun 17]. Available from: http://www.eleanorcrookfoundation.org/s/ecf-global-nutrition-survey_Oct2018.pdf.
10. The State of Acute Malnutrition. Where are we in treating children with SAM? London: No Wasted Lives Coalition; 2019 [cited 2019 Jul 3]. Available from: https://acutemalnutrition.org/en/countries.
11. Shekar M, Kakietek J, Eberwein JD, Walters D. An investment framework for nutrition: reaching the global targets for stunting, anemia, breastfeeding, and wasting. Washington (DC): World Bank Group; 2017 [cited 2020 Jun 1]. Available from: https://www.worldbank.org/en/topic/nutrition/publication/an-investment-framework-for-nutrition-reaching-the-global-targets-for-stunting-anemia-breastfeeding-wasting.
12. Olofin I, McDonald C, Ezzati M, Flaxman S, Black R, Fawzi W, et al. Associations of suboptimal growth with all-cause and cause-specific mortality in children under five years: a pooled analysis of ten prospective studies. PLoS ONE. 2013;8(5):64636.
13. Cichon B, Fabiansen C, Yaméogo CW, Rytter MJH, Ritz C, Briend A, et al. Children with moderate acute malnutrition have inflammation not explained by maternal reports of illness and clinical symptoms: a cross-sectional study in Burkina Faso. BMC Nutr. 2016;2:57.
14. James P, Sadler K, Wondafrash M, Argaw A, Luo H, Geleta B, et al. Children with moderate acute malnutrition with no access to supplementary feeding programmes experience high rates of deterioration and no improvement: results from a prospective cohort study in rural Ethiopia. PLoS ONE. 2016;11(4):0153530.
15. Chang C, Trehan I, Wang R, Thakwalakwa C, Maleta K, Deitchler M, et al. Children successfully treated for moderate acute malnutrition remain at risk for malnutrition and death in the subsequent year after recovery. J Nutr. 2013;143:215–20. doi: 10.3945/jn.112.168047 23256140
16. Lelijveld N, Hendrixson DT, Godbout C, Los A, Leppanen JM, Koroma A, et al. Defining and treating “high-risk” moderate acute malnutrition using expanded admission criteria (Hi-MAM Study): a cluster-randomised controlled trial protocol. Field Exchange. 2019 Jul 26 [cited 2020 Jun 17]. Available from: https://www.ennonline.net/fex/60/himamstudy.
17. World Health Organization. Guideline: assessing and managing children at primary health-care facilities to prevent overweight and obesity in the context of the double burden of malnutrition. Geneva: World Health Organization; 2017 Oct 3 [cited 2019 Apr 9]. Available from: https://www.who.int/nutrition/publications/guidelines/children-primaryhealthcare-obesity-dbm/en/.
18. World Health Organization. Technical note: supplementary foods for the management of moderate acute malnutrition in infants and children 6–59 months of age. Geneva: World Health Organization; 2012 [cited 2020 Jun 17]. Available from: http://apps.who.int/iris/handle/10665/75836.
19. United Nations Children’s Fund, World Food Programme. Updated guidance on mutual areas of responsibility and collaboration for nutrition: an update to the UNICEF, WFP 2005 MOU. New York: United Nations Children’s Fund; 2011.
20. Shoham J, Dolan C, Gostelow L. Managing acute malnutrition at scale: a review of donor and government financing arrangements. London: Overseas Development Institute Humanitarian Practice Network; 2013 May [cited 2019 Apr 9]. Available from: https://odihpn.org/wp-content/uploads/2013/05/NP75_cover_web.pdf.
21. Maust A, Koroma A, Abla C, Molokwu N, Ryan KN, Singh L, et al. Severe and moderate acute malnutrition can be successfully managed with an integrated protocol in Sierra Leone. J Nutr. 2015;145(11):2604–9. doi: 10.3945/jn.115.214957 26423737
22. Daures M, Phelan K, Issoufou M, Kouanda S, Sawadogo O, Issaley K, et al. New approach to simplifying and optimising acute malnutrition treatment in children aged 6–59 months: the OptiMA single-arm proof-of-concept trial in Burkina Faso. Br J Nutr. 2020;123(7):756–67. doi: 10.1017/S0007114519003258 31818335
23. Briend A, Alvarez JL, Avril N, Bahwere P, Bailey J, Berkley J, et al. Low mid-upper arm circumference identifies children with a high risk of death who should be the priority target for treatment. BMC Nutr. 2016;2:63. doi: 10.1186/s40795-016-0101-7
24. Bliss J, Lelijveld N, Briend A, Kerac M, Manary M, McGrath M, et al. Use of mid-upper arm circumference by novel community platforms to detect, diagnose, and treat severe acute malnutrition in children: a systematic review. Glob Health Sci Pract. 2018;6(3):552–64. doi: 10.9745/GHSP-D-18-00105 30185435
25. Chase R, Kerac M, Grant A, Manary M, Briend A, Opondo C, et al. Acute malnutrition recovery energy requirements based on mid-upper arm circumference: secondary analysis of feeding program data from 5 countries, Combined Protocol for Acute Malnutrition Study (ComPAS) Stage 1. PLoS ONE. 2020;15(6):e0230452. doi: 10.1371/journal.pone.0230452 32492023
26. Goossens S, Bekele Y, Yun O, Harczi G, Ouannes M, Shepherd S. Mid-upper arm circumference based nutrition programming: evidence for a new approach in regions with high burden of acute malnutrition. PLoS ONE. 2012;7(11):e49320. doi: 10.1371/journal.pone.0049320 23189140
27. Binns P, Dale N, Hoq M, Banda C, Myatt M. Relationship between mid upper arm circumference and weight changes in children aged 6–59 months. Arch Public Health. 2015;73:54. doi: 10.1186/s13690-015-0103-y 26693279
28. Burza S, Mahajan R, Marino E, Sunyoto T, Shandilya C, Tabrez M, et al. Community‐based management of severe acute malnutrition in India: new evidence from Bihar. Am J Clin Nutr. 2015;101(4):847–59. doi: 10.3945/ajcn.114.093294 25833981
29. Ashworth A. Efficacy and effectiveness of community-based treatment of severe malnutrition. Food Nutr Bull. 2006;27(3 Suppl):S24–48. doi: 10.1177/15648265060273S303 17076212
30. James PT, Van den Briel N, Rozet A, Israël AD, Fenn B, Navarro-Colorado C. Low‐dose RUTF protocol and improved service delivery lead to good programme outcomes in the treatment of uncomplicated SAM: a programme report from Myanmar. Matern Child Nutr. 2015;11:859–69. doi: 10.1111/mcn.12192 25850698
31. Kangas ST, Salpéteur C, Nikièma V, Talley L, Ritz C, Friis H, et al. Impact of reduced dose of ready-to-use therapeutic foods in children with uncomplicated severe acute malnutrition: a randomised non-inferiority trial in Burkina Faso. PLoS Med. 2019;16(8):e1002887. doi: 10.1371/journal.pmed.1002887 31454351
32. Global Nutrition Cluster MAM Task Force. Moderate acute malnutrition: a decision tool for emergencies. Geneva: Global Nutrition Cluster; 2017 [cited 2020 Jun 17]. Available from: https://reliefweb.int/sites/reliefweb.int/files/resources/DECISION-TOOL-FOR-MAM_w-exceptional-cicumstances_-May-2017-update-final1.pdf.
33. Bailey J, Lelijveld N, Marron B, Onyo P, Ho LS, Manary M, et al. Combined Protocol for Acute Malnutrition Study (ComPAS) in rural South Sudan and urban Kenya: study protocol for a randomized controlled trial. Trials. 2018;19(1):251. doi: 10.1186/s13063-018-2643-2 29690916
34. Lelijveld N, Bailey J, Mayberry A, Trenouth L, N’Diaye DS, Haghparast-Bidgoli H, et al. The “ComPAS Trial” combined treatment model for acute malnutrition: study protocol for the economic evaluation. Trials.2018;19(1):252. doi: 10.1186/s13063-018-2594-7 29690899
35. Southern Sudan Centre for Census, Statistics and Evaluation. Fifth Sudan population and housing census 2008. Juba: Southern Sudan Centre for Census, Evaluation and Statistics; 2008.
36. Kenya National Bureau of Statistics, Society for International Development. Exploring Kenya’s inequalities: pulling apart or pooling together? Nairobi: Kenya National Bureau of Statistics; 2013 [cited 2020 Jun 17]. Available from: http://inequalities.sidint.net/kenya/wp-content/uploads/sites/3/2013/10/Preliminary%20pages.pdf.
37. World Health Organization. Integrated management of childhood illness: chart booklet. Geneva: World Health Organization; 2014 [cited 2019 Apr 9]. Available from: http://www.who.int/maternal_child_adolescent/documents/IMCI_chartbooklet/en/.
38. Envelope Sealed. Create a randomisation list. London: Sealed Envelope; 2020 [cited 2020 Jun 17]. Available from: https://sealedenvelope.com/simple-randomiser/v1/lists.
39. Myatt M, Guevarra E, Fieschi L, Norris A, Guerrero S, Schofield L, et al. Semi-Quantitative Evaluation of Access and Coverage (SQUEAC)/Simplified Lot Quality Assurance Sampling Evaluation of Access and Coverage (SLEAC) Technical Reference. Washington (DC): Food and Nutrition Technical Assistance; 2012 Oct [cited 2020 Jun 1]. Available from: https://www.fantaproject.org/sites/default/files/resources/SQUEAC-SLEAC-Technical-Reference-Oct2012_0.pdf.
40. Sphere Association. The Sphere handbook: humanitarian charter and minimum standards in humanitarian response. 2018 edition. Geneva: Sphere Association; 2018 [cited 2020 Jun 17]. Available from: https://spherestandards.org/wp-content/uploads/Sphere-Handbook-2018-EN.pdf.
41. Campbell MK, Thomson S, Ramsay CR, MacLennan GS, Grimshaw JM. Sample size calculator for cluster-randomized trials. Comput Biol Med. 2004;34(2):113–25. doi: 10.1016/S0010-4825(03)00039-8 14972631
42. Rutterford C, Copas A, Eldrige S. Methods for sample size determination in cluster-randomized trials. Int J Epidemiol. 2015;44(3):1051–67. doi: 10.1093/ije/dyv113 26174515
43. Dimagi. CommCare. Cambridge (MA): Dimagi; 2020 [cited 2020 Jun 17]. Available from: https://www.dimagi.com/commcare/.
44. Piaggio G, Elbourne DR, Pocock SJ, Evans SJ, Altman DG, CONSORT Group. Reporting of noninferiority and equivalence randomized trials: extension of the CONSORT 2010 statement. JAMA. 2012;308(24):2594–604. doi: 10.1001/jama.2012.87802 23268518
45. Schumi J, Wittes JT. Through the looking glass: understanding non-inferiority. Trials. 2011;12(1):106.
46. StataCorp. Stata Statistical Software. Version 13.1. College Station (TX): StataCorp; 2013.
47. Leroy JL. ZSCORE06: Stata command for the calculation of anthropometric z-scores using the 2006 WHO child growth standards. EconPapers. 2011 [cited 2020 June 18]. Available from: https://econpapers.repec.org/software/bocbocode/s457279.htm.
48. Wilford R, Golden K, Walker KG. Cost-effectiveness of community-based management of acute malnutrition in Malawi. Health Policy Plan. 2012;27(2):127–37. doi: 10.1093/heapol/czr017 21378101
49. Puett C, Sadler K, Alderman H, Coates J, Fiedler J, Myatt M. Cost-effectiveness of the community-based management of severe acute malnutrition by community health workers in southern Bangladesh. Health Policy Plan. 2013;28(4):386–99. doi: 10.1093/heapol/czs070 22879522
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