Competing risk events in antimalarial drug trials in uncomplicated Plasmodium falciparum malaria: a WorldWide Antimalarial Resistance Network individual participant data meta-analysis.
Authors
Dahal, PSimpson, JA
Abdulla, S
Achan, J
Adam, I
Agarwal, A
Allan, R
Anvikar, AR
Arinaitwe, E
Ashley, EA
Awab, GR
Bassat, Q
Bjorkman, A
Bompart, F
Borrmann, S
Bousema, T
Broek, I
Bukirwa, H
Carrara, VI
Corsi, M
Cot, M
D'Alessandro, U
Davis, TME
de Wit, M
Deloron, P
Desai, M
Dimbu, PR
Djalle, D
Djimde, A
Dorsey, G
Doumbo, OK
Drakeley, CJ
Duparc, S
Edstein, MD
Espie, E
Faiz, A
Falade, C
Fanello, C
Faucher, JF
Faye, B
de Jesus Fortes, F
Gadalla, NB
Gaye, O
Gil, JP
Greenwood, B
Grivoyannis, A
Hamed, K
Hien, TT
Hughes, D
Humphreys, G
Hwang, J
Ibrahim, ML
Janssens, B
Jullien, V
Juma, E
Kamugisha, E
Karema, C
Karunajeewa, HA
Kiechel, JR
Kironde, F
Kofoed, PE
Kremsner, PG
Lameyre, V
Lee, SJ
Marsh, K
Martensson, A
Mayxay, M
Menan, H
Mens, P
Mutabingwa, TK
Ndiaye, JL
Ngasala, BE
Noedl, H
Nosten, F
Offianan, AT
Oguike, M
Ogutu, BR
Olliaro, P
Ouedraogo, JB
Piola, P
Plowe, CV
Plucinski, MM
Pratt, OJ
Premji, Z
Ramharter, M
Rogier, C
Rombo, L
Rosenthal, PJ
Sawa, P
Schramm, P
Sibley, C
Sinou, V
Sirima, S
Smithuis, F
Staedke, SG
Sutanto, I
Talisua, AO
Tarning, J
Taylor, WRJ
Temu, E
Thriemer, KL
Thuy, NN
Udhayakumar, V
Ursing, J
van Herp, M
van Vugt, M
Whitty, C
William, Y
Winnips, C
Zongo, I
Guerin, P
Price, RN
Stepniewska, K
Issue Date
2019-07-05Submitted date
2019-08-20
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Malaria JournalAbstract
BACKGROUND: Therapeutic efficacy studies in uncomplicated Plasmodium falciparum malaria are confounded by new infections, which constitute competing risk events since they can potentially preclude/pre-empt the detection of subsequent recrudescence of persistent, sub-microscopic primary infections. METHODS: Antimalarial studies typically report the risk of recrudescence derived using the Kaplan-Meier (K-M) method, which considers new infections acquired during the follow-up period as censored. Cumulative Incidence Function (CIF) provides an alternative approach for handling new infections, which accounts for them as a competing risk event. The complement of the estimate derived using the K-M method (1 minus K-M), and the CIF were used to derive the risk of recrudescence at the end of the follow-up period using data from studies collated in the WorldWide Antimalarial Resistance Network data repository. Absolute differences in the failure estimates derived using these two methods were quantified. In comparative studies, the equality of two K-M curves was assessed using the log-rank test, and the equality of CIFs using Gray's k-sample test (both at 5% level of significance). Two different regression modelling strategies for recrudescence were considered: cause-specific Cox model and Fine and Gray's sub-distributional hazard model. RESULTS: Data were available from 92 studies (233 treatment arms, 31,379 patients) conducted between 1996 and 2014. At the end of follow-up, the median absolute overestimation in the estimated risk of cumulative recrudescence by using 1 minus K-M approach was 0.04% (interquartile range (IQR): 0.00-0.27%, Range: 0.00-3.60%). The overestimation was correlated positively with the proportion of patients with recrudescence [Pearson's correlation coefficient (ρ): 0.38, 95% Confidence Interval (CI) 0.30-0.46] or new infection [ρ: 0.43; 95% CI 0.35-0.54]. In three study arms, the point estimates of failure were greater than 10% (the WHO threshold for withdrawing antimalarials) when the K-M method was used, but remained below 10% when using the CIF approach, but the 95% confidence interval included this threshold. CONCLUSIONS: The 1 minus K-M method resulted in a marginal overestimation of recrudescence that became increasingly pronounced as antimalarial efficacy declined, particularly when the observed proportion of new infection was high. The CIF approach provides an alternative approach for derivation of failure estimates in antimalarial trials, particularly in high transmission settings.Publisher
BioMed CentralPubMed ID
31277713Language
enISSN
1475-2875ae974a485f413a2113503eed53cd6c53
10.1186/s12936-019-2837-4
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