214 159 # HR 2.28 [1.71 3.04] pt.4 <- 57 / 20868 # exposure (hypertension) pc.4 <- 1053 / 1664488 # control (no hypertension) # 1 year incidence probability pt.1 <- cumulative_p(pt.4, 1 / 4) pc.1 <- cumulative_p(pc.4, 1 / 4) rr_estimate <- rr_from_hr(0.0002, .003, 2.28) # 2.278893 max.bias(0.0002, .003, 2.28, step = .0001) |> pull(bias) |> max() # 1.000413 # lower bound lb_max_bias <- max.bias(0.0002, .003, 1.71, step = .0001) |> pull(bias) |> max() # 1.000413 (rr_bc_lb <- rr_from_hr(0.0002, .003, 1.71)) # 1.709406 lb_rr_bc <- rr_bc_lb / lb_max_bias # upper bound ub_max_bias <- max.bias(0.0002, .003, 3.04, step = .0001) |> pull(bias) |> max() # 1.000413 (rr_bc_ub <- rr_from_hr(0.0002, .003, 3.04)) # 3.038159 ub_rr_bc <- rr_bc_ub * ub_max_bias # Estimation of the main effect of the intervention rr_c.a <- rr_c_a(pb_a_treat, pb_a_ctrl, rr_estimate) # 0.7341925 # Estimation of confidence interval df <- map_dbl(1:10000, \(x) get_ca_ci(lb_rr_bc, ub_rr_bc)) quantile(df, probs = c(0.025, 0.50, 0.975)) # 0.6502432 0.7257125 0.8162945 References: 1. GoYK study: Boonstra MD, Gurgel do Amaral MS, Navis GJ, et al. Effectiveness of a health literacy intervention targeting both chronic kidney disease patients and health care professionals in primary and secondary care: a quasi-experimental study. [Unpublished results] 2. Kanno A, Kikuya M, Ohkubo T, et al. Pre-hypertension as a significant predictor of chronic kidney disease in a general population: the Ohasama Study. Nephrol Dial Transplant. 2012;27(8):3218-23. 3. Kim CS, Kim B, Choi HS, et al. Cumulative hypertension burden and risk of end-stage renal disease. Hypertens Res. 2021;44(12):1652-61. 4. VanderWeele TJ. Optimal approximate conversions of odds ratios and hazard ratios to risk ratios. Biometrics. 2020;76(3):746-52.
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