Reference intervals for plasma proteins: similarities and differences between adult Caucasian and Asian Indian males in Yorkshire, UK

Exploring ethnic differences in the distribution of blood test results in healthy adult populations to inform earlier cancer detection: a systematic review

BACKGROUND

In primary care, health professionals use blood tests to investigate nonspecific presentations to inform referral decisions. Reference ranges for the commonly used blood tests in western countries were developed in predominately White populations, and so may perform differently when applied to non-White populations. Knowledge of ethnic variation in blood test results in healthy/general populations could help address ethnic inequalities in cancer referral for diagnosis and outcomes.

OBJECTIVE

This systematic review explored evidence of ethnic differences in the distribution of selected blood test results among healthy/general populations to inform future research aimed at addressing inequalities in cancer diagnosis.

METHODS

We searched PubMed and EMBASE to identify studies reporting measures of haemoglobin, MCV, calcium, albumin, platelet count, and CRP in nondiseased adults from at least 2 different ethnic groups. Two reviewers independently screened studies, completed data extraction and quality assessment using an adapted Newcastle-Ottawa scale. Participants were stratified into White, Black, Asian, Mixed, and Other groups. Data were synthesised narratively and meta-analyses were conducted where possible.

RESULTS

A total of 47 papers were included. Black men and women have lower average values of haemoglobin, MCV, and albumin, and higher average values of CRP relative to their White counterparts. Additionally, Black men have lower average haemoglobin than Asian men, whereas Asian women have lower average CRP values when compared with White women.

CONCLUSIONS

There is evidence of ethnic differences in average values of haemoglobin, MCV, CRP, and albumin in healthy/general populations. Further research is needed to explore the reasons for these differences. Systematic review registration: CRD42021274580.

Biological variables influencing the estimation of reference limits

Reference limits (RLs) are required to evaluate laboratory results for medical decisions. The establishment of RL depends on the pre-analytical and the analytical conditions. Furthermore, biological characteristics of the sub-population chosen to provide the reference samples may influence the RL. The most important biological preconditions are gender, age, chronobiological influences, posture, regional and ethnic effects. The influence of these components varies and is often neglected. Therefore, a list of biological variables is collected from the literature and their influence on the estimation of RL is discussed. Biological preconditions must be specified if RL are reported as well for directly as for indirectly estimated RL. The influence of biological variables is especially important if RL established by direct methods are compared with those derived from indirect techniques. Even if these factors are not incorporated into the estimation of RL, their understanding can assist the interpretation of laboratory results of an individual.

Harmonization of units and reference intervals of plasma proteins: state of the art from an External Quality Assessment Scheme

Background:

The need to harmonize laboratory information is particularly intense in the field of plasma proteins, considering their clinical impact and relevance in monitoring diseases.

Methods:

We evaluated units and reference intervals (RIs) utilized by participants of the External Quality Assessment Scheme (EQAS) for plasma proteins of the Centre of Biomedical Research. Moreover, we evaluated inter-laboratory analytical variability from 2001 to 2017.

Results:

The census of participants’ units employed in 2017 showed that for albumin (ALB), ~66% of laboratories still used dL instead of L, and for most other proteins, ~70% still expressed the results in mg/dL. Laboratories primarily used the RIs reported in the packaging inserts of their analytical systems, but for each protein, there was a wide variability of RIs, also among laboratories using the same analytical method. Mean CVs% of the 13 certified proteins in the last five EQA cycles ranged from 3.8% of haptoglobin (HPT) to 12.4% of α1-antitrypsin (AAT) and decreased from 2001 to 2017 for most of them, in particular for C3, ALB, α2-macroglobulin (A2M), HPT and transferrin (TRF).

Conclusions:

In the face of a reduction in inter-laboratory variability for a lot of proteins, there has not been a substantial change in the units and in the RIs used by the participants. To change old habits is difficult and requires coordination and collaboration. The EQAS plays an important role in the assessment and monitoring of all elements that contribute to the formulation of laboratory information and may be useful to contribute to their harmonization.

'Aussie normals': an a priori study to develop clinical chemistry reference intervals in a healthy Australian population

Development of reference intervals is difficult, time consuming, expensive and beyond the scope of most laboratories. The Aussie Normals study is a direct a priori study to determine reference intervals in healthy Australian adults. All volunteers completed a health and lifestyle questionnaire and exclusion was based on conditions such as pregnancy, diabetes, renal or cardiovascular disease. Up to 91 biochemical analyses were undertaken on a variety of analytical platforms using serum samples collected from 1856 volunteers. We report on our findings for 40 of these analytes and two calculated parameters performed on the Abbott ARCHITECTci8200/ci16200 analysers. Not all samples were analysed for all assays due to volume requirements or assay/instrument availability. Results with elevated interference indices and those deemed unsuitable after clinical evaluation were removed from the database. Reference intervals were partitioned based on the method of Harris and Boyd into three scenarios, combined gender, males and females and age and gender. We have performed a detailed reference interval study on a healthy Australian population considering the effects of sex, age and body mass. These reference intervals may be adapted to other manufacturer's analytical methods using method transference.

The theory of reference values: an unfinished symphony

The history of the theory of reference values can be written as an unfinished symphony. The first movement, allegro con fuoco, played from 1960 to 1980: a mix of themes devoted to the study of biological variability (intra-, inter-individual, short- and long-term), preanalytical conditions, standardization of analytical methods, quality control, statistical tools for deriving reference limits, all of them complex variations developed on a central melody: the new concept of reference values that would replace the notion of normality whose definition was unclear. Additional contributions (multivariate reference values, use of reference limits from broad sets of patient data, drug interferences) conclude the movement on the variability of laboratory tests. The second movement, adagio, from 1980 to 2000, slowly develops and implements initial works. International and national recommendations were published by the IFCC-LM (International Federation of Clinical Chemistry and Laboratory Medicine) and scientific societies [French (SFBC), Spanish (SEQC), Scandinavian societies…]. Reference values are now topics of many textbooks and of several congresses, workshops, and round tables that are organized all over the world. Nowadays, reference values are part of current practice in all clinical laboratories, but not without difficulties, particularly for some laboratories to produce their own reference values and the unsuitability of the concept with respect to new technologies such as HPLC, GCMS, and PCR assays. Clinicians through consensus groups and practice guidelines have introduced their own tools, the decision limits, likelihood ratios and Reference Change Value (RCV), creating confusion among laboratorians and clinicians in substituting reference values and decision limits in laboratory reports. The rapid development of personalized medicine will eventually call for the use of individual reference values. The beginning of the second millennium is played allegro ma non-troppo from 2000 to 2012: the theory of reference values is back into fashion. The need to revise the concept is emerging. The manufacturers make a friendly pressure to facilitate the integration of Reference Intervals (RIs) in their technical documentation. Laboratorians are anxiously awaiting the solutions for what to do. The IFCC-LM creates Reference Intervals and Decision Limits Committee (C-RIDL) in 2005. Simultaneously, a joint working group IFCC-CLSI is created on the same topic. In 2008 the initial recommendations of IFCC-LM are revised and new guidelines are published by the Clinical and Laboratory Standards Institute (CLSI C28-A3). Fundamentals of the theory of reference values are not changed, but new avenues are explored: RIs transference, multicenter reference intervals, and a robust method for deriving RIs from small number of subjects. Concomitantly, other statistical methods are published such as bootstraps calculation and partitioning procedures. An alternative to recruiting healthy subjects proposes the use of biobanks conditional to the availability of controlled preanalytical conditions and of bioclinical data. The scope is also widening to include veterinary biology! During the early 2000s, several groups proposed the concept of 'Universal RIs' or 'Global RIs'. Still controversial, their applications await further investigations. The fourth movement, finale: beyond the methodological issues (statistical and analytical essentially), important questions remain unanswered. Do RIs intervene appropriately in medical decision-making? Are RIs really useful to the clinicians? Are evidence-based decision limits more appropriate? It should be appreciated that many laboratory tests represent a continuum that weakens the relevance of RIs. In addition, the boundaries between healthy and pathological states are shady areas influenced by many biological factors. In such a case the use of a single threshold is questionable. Wherever it will apply, individual reference values and reference change values have their place. A variation on an old theme! It is strange that in the period of personalized medicine (that is more stratified medicine), the concept of reference values which is based on stratification of homogeneous subgroups of healthy people could not be discussed and developed in conjunction with the stratification of sick patients. That is our message for the celebration of the 50th anniversary of Clinical Chemistry and Laboratory Medicine. Prospects are broad, enthusiasm is not lacking: much remains to be done, good luck for the new generations!

Hematological and biochemical parameters in apparently healthy Indian population: defining reference intervals

Clinical reference intervals among Indian population are poorly defined. Therefore, there is an urgent need to establish local clinical laboratory reference intervals for healthy Indian population. The present study aimed to identify the 95 % reference interval for hematological and biochemical parameters in apparently healthy Indian population. We undertook a multicentric cross-sectional study conducted at Apollo Hospitals Educational and Research Foundation across India. Of which 10,665 reference individuals identified as healthy by physicians. The 95 % of the reference distribution was estimated using 2.5th and 97.5th percentile reference limits. The 95 % reference intervals for hemoglobin (Males: 12.3-17 g/dL; Females: 9.9-14.3 g/dL), platelet count (Males: 1.3-3.8; Females: 1.3-4.2 Lakhs/µL), erythrocyte sedimentation rate (Males: 2-22; Females: 4-55 mm/h), serum uric acid in males: 3.5-8.2 mg/dL, gamma glutamyl transferase (Males: 13-61 U/L), fasting blood glucose (Males: 78-110 mg/dL), total cholesterol (Males: 115-254 mg/dL), low density lipoprotein (Males: 60-176 mg/dL) and triglycerides (Males: 55-267 mg/dL, Females: 52-207 mg/dL) were different from currently used reference values. Additionally need for gender based partitioning were observed for triglycerides and gamma glutamyl transferase. The observed findings are of clinical significance and it needs to be validated with additional community based studies.

Reference ranges of coagulation tests

Reference ranges are a set of values that correctly include most of the subjects with characteristics similar to the reference group and exclude the others. When accurate, reference ranges aid physicians to interpret results of clinical measurements and thus establish diagnosis. However, obtaining accurate reference ranges is a very demanding procedure. This chapter provides basic definitions and theories as well as a step-by-step procedure for the analysis of reference values and determination of reference ranges of coagulation, focusing on quantitative clinical laboratory assays. Preanalytical and analytical factors as well as dependence on the age influencing reference values for coagulation assays and their transference are discussed.

alpha1-acid glycoprotein as a putative biomarker for monitoring the development of the type II reactional stage of leprosy

Leprosy, a spectral disease manifested on the basis of host immune responses, is complicated by its reactional stages, namely type I reversal reaction (RR) and type II erythema nodosum leprosum (ENL). These reactional stages are characterized by uncontrolled and aberrant immune responses. Biomarkers for reactional stages would aid in early diagnosis, efficient treatment, prevention of neurological complications and prediction of predisposition to reactional stages. In this study, comparative analysis of the serum proteome of leprosy patients by two-dimensional electrophoresis (2DE) followed by mass spectrometry showed differential expression of acute-phase protein alpha (1)-acid glycoprotein (AGP; also known as orosomucoid). AGP levels in untreated ENL cases were significantly higher than in lepromatous leprosy (LL; a non-reactional disease stage) (P=0.0126), RR (P=0.0176) and healthy controls (P=0.0030). These data were confirmed using ELISA. The levels of AGP decreased to normal levels after treatment with multidrug therapy and thalidomide (P =0.0167). In a follow-up study, AGP levels, which were high in the untreated ENL stage, decreased significantly at 5 days ( P=0.0084) and 21 days (P=0.0027) post-treatment. A stage-dependent increase in AGP in an LL patient who progressed into the ENL stage was also shown. Glycosylation analysis by 2DE showed differential expression of acidic glycoforms of AGP in untreated ENL cases. Changes in AGP concentration and differential expression of isoforms correlated with the inflammatory condition in ENL and also with the treatment regimen. Thus, initial validation of AGP as an ENL-specific biomarker and treatment indicator was shown in this study.

Serum beta2-microglobulin measured by immunonephelometry: expression patterns and reference intervals in healthy adults

BACKGROUND

Serum beta2-microglobulin (beta2m) has been established as a marker of disease activity in malignancies, autoimmune conditions and infections. Despite its important role in prognosis assessment and disease monitoring, relatively few studies are available on its expression in healthy individuals. Furthermore, interpretation of results is hampered by the variety in reference limits due to differences in methodology, sample population and statistics.

METHODS

Serum beta2m concentrations were measured using a microparticle-enhanced immunonephelometric method in 183 healthy blood donors aged 29-75 years.

RESULTS

The median beta2m concentration was 1.67 (0.88-2.75) mg/L with no difference between men and women (1.71 mg/L vs. 1.62 mg/L, p<0.07). A linear correlation was found between beta2m and age (p<0.0001), serum concentrations significantly higher in older subjects (1.55, 1.59, 1.70, and 1.87 mg/L in age groups of 29-40, 40-50, 50-60 and 60-75 years, respectively, p<0.0001). Reference intervals obtained by non-parametric estimation after partitioning by age were 1.02-2.46 mg/L vs. 1.29-2.70 mg/L in younger (29-49 years) vs. older (50-75 years) individuals.

CONCLUSIONS

These data can help standardise beta2m reference limits and support age-adjusted comparisons in clinical studies.

Whether western normative laboratory values used for clinical diagnosis are applicable to Indian population? An overview on reference interval

Reference Intervals denote normative values related to laboratory parameters/analytes used by diagnostic centers for clinical diagnosis. International guidelines recommend that every country must establish reference intervals for healthy individuals belonging to a group of homogeneous population. Considering enormous racial and ethnic diversity of Indian population, it is mandatory to establish reference intervals specific to Indian population. The overview on reference interval describes why the national organizations in India need to initiate nationwide efforts to establish its own laboratory standards for apparently healthy reference individuals belonging to our polygenetic, polyethnic, polyracial, multilinguistic and multicultural predominantly rural and appreciable urban Indian population with varied dietary habits.

Partitioning reference values for several subpopulations using cluster analysis

BACKGROUND

A crucial question when developing reference intervals is whether different subpopulations need their own reference interval or if a single joint reference interval can be used. It is reasonable to use partitioned reference intervals in situations where a single interval results in considerable variation in sensitivity between subpopulations. The aim of partitioning is to harmonize the sensitivity of the reference intervals, i.e., to make the sensitivity similar for all patients, regardless of patient characteristics. Statistical criteria to identify when partitioning is adequate have been developed over the last two decades. These criteria are applicable when considering two subpopulations, but recently a procedure for considering several subpopulations has been developed. When several subpopulations are considered, there is a possibility that some subpopulations could form a group or cluster that could share a common reference interval. However, there is no formal systematic approach to indicate how to divide these subpopulations into clusters. The aim of this study was to suggest such a systematic approach for clustering.

METHODS

A clustering technique was applied to data including several subpopulations. The technique is based on measuring the distance between separated reference limits and successively pooling subpopulations divided by short distances. A cluster is defined by a group of subpopulations that are close to each other and that differ from subpopulations in another cluster. A cluster recruits new subpopulations as long as the subpopulations can be pooled without violating a partitioning criterion.

CONCLUSIONS

We have suggested a procedure for partitioning a number of Gaussian (or Gaussian-transformable) subpopulations into clusters. This is the only formalized procedure indicating how to analyze several subpopulations and identify a suitable number of groups and reference intervals. Using a computer program developed for partitioning issues, the approach was easy to adopt.