Black People

Our goal was to compare the current CKD-EPI eGFRcr, eGFRcys, and eGFRcr-cys equations with equations developed with the use of two new approaches for GFR estimation that do not involve race.^{5 (link),9 (link)} As we described previously, the current approach to the development of CKD-EPI equations has been to model eGFR with the use of least-squares linear regression to relate log-transformed measured GFR to log-transformed filtration markers, age, sex, and race with separate slopes for higher as compared with lower levels of creatinine and cystatin C.^{5 (link),9 (link)} Race is an explanatory variable in the current eGFRcr and eGFRcr-cys equations but not in the current eGFRcys equation.
The first set of new equations uses the same coefficients for the intercept, age, sex and creatinine level as in the current eGFRcr and eGFRcr-cys equations but removes the Black race coefficient in computing eGFR, thereby assigning the eGFRcr and eGFRcr-cys values for non-Black persons to Black persons. For the second set of new equations, we fit new models using eGFRcr and eGFRcr-cys by means of the same regression function as the current equations but without inclusion of race as an explanatory variable. In total, we evaluated seven equations (three current and four new equations). Because all equations were developed by the CKD-EPI research group, we refer to them only by the filtration marker or markers (creatinine [eGFRcr], cystatin C [eGFRcys], or creatinine–cystatin C [eGFRcr-cys]) and the demographic factors (age, sex, and race [ASR] or age and sex [AS]) that were used in their development. We use the term non-Black (NB) to refer to ASR equations that were fit with a race term but in which the Black race coefficient was removed for computation of eGFR. Additional details are provided in the Methods section in the Supplementary Appendix.
In the development data sets, we assessed bias (systematic error) as the difference between measured GFR and eGFR and assessed model fit using root-mean-square error.^{5 (link),9 (link)} In the validation data set, we assessed accuracy overall and within race groups as bias, percentage of estimates less than 30% different from measured GFR (P₃₀, with 1−P₃₀ corresponding to large errors that may be clinically significant), and agreement of eGFR with measured GFR categories using guideline-recommended GFR stages (<30, 30 to 44, 45 to 59, 60 to 89, and >90 ml per minute per 1.73 m² of body-surface area).⁸ A P₃₀ value of 80 to 90% is considered to be acceptable for GFR evaluation in many circumstances, and a P₃₀ value of 90% or higher is preferred; these values correspond to approximately 60 to 70% agreement and more than 70% agreement of eGFR with measured GFR in GFR categories, respectively.^{5 (link),8 ,9 (link)} We also focused on differential bias (systematic differences) between race groups because it could lead to systematic differences in treatment for the same measured GFR level. Confidence intervals for bias were calculated by means of bootstrap methods. We assessed accuracy in subgroups according to eGFR (as defined above), age (<40, 40 to 65, and >65 years), sex, and body-mass index (BMI, the weight in kilograms divided by the square of the height in meters: ≤25, 25 to <30, and ≥30).
In sensitivity analyses, we weighted the proportion of Black participants in the development data set from 0 to 100% to evaluate the effect on accuracy. In the validation data set, we calibrated measured GFR to account for differences between measurement methods as compared with the development data sets,^{5 (link),9 (link),23 (link)} and we compared equations that were developed by other research groups to estimate GFR in adults.^{24 (link)–28 (link)}

Pilot studies conducted during the planning stages for BT10 in 1989 and 1990 examined several issues in an attempt to seek clarity on the anticipated numbers of children who could be enrolled into a cohort and the potential for their follow-up. These included: the monthly birth rate and seasonality of births in Soweto-Johannesburg, the scope and accuracy of routinely collected health services and local ordinance data, the feasibility and logistics of follow-up, and estimates of sample losses, at least over the short-term.3 (link) These studies indicated, amongst others, that an average of 2680 children were born each month within the defined study area; random patterns of births pertained amongst all groups of people, except for October, during which a significant increase in births occurred;23 approximately 16% of hospital deliveries were not recorded in routine delivery ward records because the births were directed through surgery and other specialised treatment services; routinely collected data was not suitable, without modification, for translation into research information because of differences in formats across service centres, lack of standardisation of measurements, unreliability, and incompleteness.24 ,25 (link) The results of the pilot studies were used to operationalise procedures for the enrolment of the birth cohort.
The pilot studies also indicated that 20% of deliveries were immediately lost to follow-up because mothers could not be found after delivery at the addresses they had given or because the addresses they had recorded were patently false. In discussion with health service personnel and as confirmed on more intensive follow-up during the first year, it was concluded that this group of people consisted of non-resident women who planned to deliver their babies in Soweto-Johannesburg for personal or social reasons, and that they were either highly mobile within the area, or that they gave false addresses when admitted to a delivery centre. Some of the reasons why women from rural and peri-urban areas came to Johannesburg-Soweto to deliver their babies were, at the time, that they continued to believe that the place of birth of their child determined access to work as was the case under Apartheid laws to control the movement and employment of black people; they assumed that the health services in the city were superior to those in rural areas, and they came to the urban areas where their migrant husbands were working to receive financial and social support during their confinement. These women returned to their customary places of residence, usually in rural areas, soon after delivery and, for this reason, could not be considered part of a residential birth cohort in Soweto-Johannesburg.
Of the remaining deliveries, 80% were traceable 9 months after their birth. The conclusion from the pilot studies was that 64% of all births, and 80% of the resident birth cohort, were likely to be traceable for at least a year. At the time of the pilot studies, the BT10 scientific team concluded that BT10, as planned, could satisfy the basic conditions of a prospective longitudinal study – that ‘the success of a prospective birth cohort depended on an initial sample size large enough, and representative of the population, to (i) reflect a sufficient range of exposures, (ii) allow for generalisability of findings, and (iii) provide sufficient subjects who have stayed in the study throughout the period of investigation, a group known as the core sample’.4 (link)^{, p. 449} In other longitudinal studies, eventual cohort sizes of around 1500 have been regarded as sufficient.15 In the light of experience gained in the course of the pilot studies, a plan for the recruitment and retention of cases was developed, and this plan has been continually refined as the study has progressed.

Wave 1 of the PATH Study included 45,971 adults and youths in the United States 12 years of age or older; data were collected from September 12, 2013, through December 15, 2014. This article reports national estimates from 32,320 adult participants (≥18 years of age) and 13,651 youth participants (12 to 17 years of age). Parent interviews were also conducted with one parent of 13,589 of the youth participants (99.5%). The parent interview collected information about the youth that was deemed to be more reliable when obtained from a parent (e.g., certain health information), as well as contextual information about the household and the parent’s own use of tobacco. Adult and youth data were collected with the use of an audio computer-assisted self-interview (ACASI), available in English and Spanish.
Address-based, area-probability sampling was used for recruitment; an in-person household screener selected youths and adults. Adult tobacco users, young adults (18 to 24 years of age), and black persons were oversampled relative to population proportions. Up to 2 youths per household were sampled unless a household included multiple births, in which case additional youths could be selected. Weighting procedures adjusted for oversampling and nonresponse. The weights were further adjusted so that the sums of the weights matched independent population totals for standard demographic groups; these totals were based on U.S. Census Bureau data. (For details on youth sampling and weighting procedures, see the Supplementary Appendix, available with the full text of this article at NEJM.org.) Combined with the use of a probability sample, the weighted data allow estimates produced by the PATH Study to be representative of the civilian, noninstitutionalized U.S. population. The weighted response rate for the household screener was 54.0%. Among screened households, the overall weighted response rate was 74.0% for the adult interview and 78.4% for the youth interview. A nonresponse bias analysis for Wave 1 can be found at http://doi.org/10.3886/ICPSR36231.
The PATH Study implemented numerous procedures to protect respondents’ privacy and confidentiality, including obtaining written informed consent from adults and written assent from youths; requiring all staff to be certified in data security, confidentiality, and privacy issues and procedures; requiring staff to sign a pledge of confidentiality; storing and transmitting data with the use of advanced data encryption; and identifying survey data and biospecimens with the use of randomly assigned identification numbers and storing identifying information in separate, secure files. Further details regarding the PATH Study design and methods are reported by Hyland et al.²⁹ The study was conducted by Westat, a contract research organization, and approved by its institutional review board.