Mass deworming for improving health and cognition of children in endemic helminth areas: A systematic review and individual participant data network meta‐analysis

BackgroundSoil transmitted (or intestinal) helminths and schistosomes affect millions of children worldwide.ObjectivesTo use individual participant data network meta‐analysis (NMA) to explore the effects of different types and frequency of deworming drugs on anaemia, cognition and growth across potential effect modifiers.Search MethodsWe developed a search strategy with an information scientist to search MEDLINE, CINAHL, LILACS, Embase, the Cochrane Library, Econlit, Internet Documents in Economics Access Service (IDEAS), Public Affairs Information Service (PAIS), Social Services Abstracts, Global Health CABI and CAB Abstracts up to March 27, 2018. We also searched grey literature, websites, contacted authors and screened references of relevant systematic reviews.Selection CriteriaWe included randomised and quasirandomised deworming trials in children for deworming compared to placebo or other interventions with data on baseline infection.Data Collection and AnalysisWe conducted NMA with individual participant data (IPD), using a frequentist approach for random‐effects NMA. The covariates were: age, sex, weight, height, haemoglobin and infection intensity. The effect estimate chosen was the mean difference for the continuous outcome of interest.ResultsWe received data from 19 randomized controlled trials with 31,945 participants. Overall risk of bias was low. There were no statistically significant subgroup effects across any of the potential effect modifiers. However, analyses showed that there may be greater effects on weight for moderate to heavily infected children (very low certainty evidence).Authors' ConclusionsThis analysis reinforces the case against mass deworming at a population‐level, finding little effect on nutritional status or cognition. However, children with heavier intensity infections may benefit more. We urge the global community to adopt calls to make data available in open repositories to facilitate IPD analyses such as this, which aim to assess effects for the most vulnerable individuals.</div

Forest plots from random-effects meta-analysis by risk factor.

<p>a. Male circumcision/Muslim religion b. History of paying for sex (men) c. Multiple sexual partners (> = 2 <i>versus</i> 0–1) d. HSV-2 e. Syphilis f. Gonorrhea g. History of genital ulcer <i>Footnotes: i) Study  =  first author, [reference #], year study was conducted. ii) Studies in table (author, publication year [reference #]): Becker, ML 2010 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Becker2" target="_blank">[<i>71</i>]</a><i>, Becker, ML 2007 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Becker1" target="_blank">[<i>13</i>]</a><i>, Brahme, R 2006 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Brahme1" target="_blank">[<i>72</i>]</a><i>, Brahme, R 2005 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Brahme2" target="_blank">[<i>73</i>]</a><i>, Dandona, L 2008 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Dandona1" target="_blank">[<i>11</i>]</a><i>, Decker, MR 2009 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Decker1" target="_blank">[<i>74</i>]</a><i>, Gangakhedkar, RR 1997 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Gangakhedkar1" target="_blank">[<i>75</i>]</a><i>, George, S 1997 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-George1" target="_blank">[<i>76</i>]</a><i>, Kumar, R 2006 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Kumar1" target="_blank">[<i>4</i>]</a><i>, Kumarasamy, N 2010 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Kumarasamy1" target="_blank">[<i>77</i>]</a><i>, Kumta, S 2010 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Kumta1" target="_blank">[<i>78</i>]</a><i>, Madhivanan, P 2005 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Madhivanan3" target="_blank">[<i>79</i>]</a><i>, Manjunath, P 2002 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Manjunath1" target="_blank">[<i>80</i>]</a><i>, Mehendale, SM 1996 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Mehendale1" target="_blank">[<i>81</i>]</a><i>, Mehta, SH 2006 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Mehta2" target="_blank">[<i>82</i>]</a><i>, Mishra, S 2009 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Mishra1" target="_blank">[<i>5</i>]</a><i>, Mukhopadhyay, S 2010 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Mukhopadhyay1" target="_blank">[<i>83</i>]</a><i>, Munro, HL 2008 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Munro1" target="_blank">[<i>12</i>]</a><i>, Nag, VL 2009 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Nag1" target="_blank">[<i>84</i>]</a><i>, Jindal, N 2007 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Jindal1" target="_blank">[<i>85</i>]</a><i>, National Family Health Survey 3 (NFHS-3) 2006 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-International1" target="_blank">[<i>64</i>]</a><i>, Panda, S 2005 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Panda2" target="_blank">[<i>86</i>]</a><i>, Ramesh, BM 2008 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Ramesh1" target="_blank">[<i>87</i>]</a><i>, Reynolds, SJ 2003 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Reynolds3" target="_blank">[<i>10</i>]</a><i>, Reynolds, SJ 2006 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Reynolds2" target="_blank">[<i>7</i>]</a><i>, Rodrigues, JJ 1995 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Rodrigues1" target="_blank">[<i>88</i>]</a><i>, Samuel, NM 2007 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Samuel1" target="_blank">[<i>89</i>]</a><i>, Sarkar, K 2006 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Sarkar1" target="_blank">[<i>90</i>]</a><i>, Schneider, JA 2010 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Schneider1" target="_blank">[<i>91</i>]</a><i>, Shahmanesh, M 2009 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Shahmanesh1" target="_blank">[<i>92</i>]</a><i>, Shepherd, ME 2003 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Shepherd1" target="_blank">[<i>93</i>]</a><i>, Shethwala, N 2009 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Shethwala1" target="_blank">[<i>94</i>]</a><i>, Solomon, S 1998 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Solomon1" target="_blank">[<i>95</i>]</a><i>, Solomon, S 2010 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Solomon2" target="_blank">[<i>96</i>]</a><i>, Talukdar, A 2007 </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044094#pone.0044094-Talukdar1" target="_blank">[<i>16</i>]</a><i>. iii) For some studies missing cases are shown where effect estimates were available but counts were not calculable from the published study or available from the authors. Some studies may appear more than once due to separate estimates for men and women.</i></p

Population attributable fraction estimates.

<p>Footnotes:</p><p>1. Pe  =  prevalence of exposure in study population.</p><p>2. PAF  =  Population attributable fraction calculated as: Pe * (OR - 1)/(Pe * (OR - 1)+1).</p

Summary table of effect estimates from random effects meta-analysis for seven risk factors.

<p>Footnote:</p><p>n =  number of studies; Results of random effects meta-analysis; p =  p-value for Egger's test for publication bias.</p

Flow of search strategy and included studies.

<p>Flow of search strategy and included studies.</p

Adult (15–49) HIV prevalence (A) and annual incidence (B) in Zimbabwe, Kenya, Malawi, and Mozambique, 1990–2009 [8].

<p>Adult (15–49) HIV prevalence (A) and annual incidence (B) in Zimbabwe, Kenya, Malawi, and Mozambique, 1990–2009 <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003459#pcbi.1003459-UNAIDS1" target="_blank">[8]</a>.</p

Factors associated with using female sex work among Indian men reporting any non-regular partner in the past year in the low-HIV states, 2006.

<p>FSW = female sex worker; PR = prevalence ratio; NRP = non-regular partner. Frequencies (sample-weighted percentages) for each variable exclude missing data.</p>a<p>Unmarried model (model n = 1591) is adjusted for age and the variables shown in the upper portion of the table; married model (model n = 906) is adjusted for age, education, and the variables shown in the lower portion of the table.</p

Adjusted prevalence ratios (95% CI) for use of female sex workers (FSW) comparing men with multiple non-regular partners (NRP) to men with one NRP in the past year in 2006.

<p>CI = confidence interval. All prevalence ratios (PR) are adjusted for age and education. PR for unmarried men in the high-HIV states is also adjusted for urban residency, employment in the transport sector, having heard of STI, receiving interpersonal STI/HIV/AIDS education in the past year, genital discharge or ulcer in the past year, and consistency of condom use with NRP in the past year. PR for married men in the high-HIV states is also adjusted for urban residency, employment in the transport sector, having heard of STI, receiving interpersonal STI/HIV/AIDS education in the past year, and consistency of condom use with NRP in the past year. PR for unmarried men in the low-HIV states is also adjusted for urban residency, employment in the transport sector, genital discharge or ulcer in the past year, and consistency of condom use with NRP in the past year. PR for married men in the low-HIV states is also adjusted for employment in the transport sector, awareness of a local HIV test centre, and consistency of condom use with NRP in the past year.</p

Age-standardized prevalence of using female sex work among Indian men reporting any non-regular partner in the past year, by region and marital status, 2006.

<p>PR = prevalence ratio; FSW = female sex worker; CI = confidence interval.</p>a<p>Percentages are sample-weighted.</p>b<p>Excludes the northeastern states.</p>c<p>Total percentages and 95% CIs are sample-weighted and standardized to the age distribution of all 3423 men in the study sample reporting any non-regular partner in the past year.</p

Factors associated with using female sex work among Indian men reporting any non-regular partner in the past year in the high-HIV states, 2006.

<p>FSW = female sex worker; PR = prevalence ratio; NRP = non-regular partner; STI = sexually transmitted infection. Frequencies (sample-weighted percentages) for each variable exclude missing data.</p>a<p>Unmarried model (model n = 352) is adjusted for age and the variables shown in the upper portion of the table; married model (model n = 399) is adjusted for age, education, consistency of condom use with spouse, and the variables shown in the lower portion of the table.</p