Post-analytical Factors Research Articles

Evaluation of the Hematology Analyzer Test Performance Using Six Sigma Metrics: A Cross Sectional Study

Abstract Introduction/Objective The six sigma metric is used to assess the performance of a measurement procedure in comparison to the medical requirement. In clinical laboratories, it can be used to assess the quality of instruments or processes. This study aims to evaluate the performance of hematology analyzers using the six sigma scale. Methods/Case Report This is a descriptive cross-sectional study wherein quality control data from hematology analyzers were obtained. The mean, standard deviation, coefficient of variation, bias and sigma value of the RBC, WBC, hemoglobin, hematocrit, and platelet parameters were determined and the performance of Beckman Coulter DxH 900 was assessed by plotting a normalized OPSpecs chart. Results (if a Case Study enter NA) The WBC and platelet parameters had sigma values of more than 6. Less stringent quality control measures could be applied these parameters which include fewer Westgard rules and fewer control runs. The RBC and hemoglobin parameters had sigma values of at least 3. The hematocrit parameter had a sigma value of less than 3. Improving this parameter could be done by performing optical channel evaluation, using multiple Westgard control rules, increasing the number of control materials and the number of runs. Conclusion This study has demonstrated the analytical performance of hematology analyzers on the six sigma scale, which in turn allows for the selection of the appropriate statistical quality control rule. Ultimately, statistical quality control is only one part of a laboratory’s quality management system. The sigma quality of the testing process, as well as choosing the appropriate control rules and number of controls, may provide the basis for the total quality control strategy of the laboratory. Other pre-analytic and post-analytic factors must also be considered in formulating a laboratory total quality control plan. This would allow the laboratory to provide the best possible quality of services to its clients by increasing efficiency, reducing wastage, and incorporating continuous changes to improve the system.

Pitfalls in Urinary Tract Cytology: Algorithmic Approach and The Paris System

Urine cytology is sensitive for detection of high-grade urothelial carcinoma. However, urine is a hostile medium for the exfoliated cells leading to degenerative changes with various interpretation challenges. Chances of misinterpretation can be avoided if the interpreter is conversant with potential pitfalls during evaluation of urine cytology. The causes may be due to pre-analytic, analytic, or post-analytic factors which include method of collection (voided versus cystoscopic versus bladder washing versus other procedures), use of preservative if any, and availability of relevant clinical history. Most common pitfalls are related to low-grade urothelial neoplasms; however, clinically critical are those which are mimickers of high-grade urothelial carcinoma (HGUC).

Preanalytical, analytical and postanalytical considerations in circulating microRNAs measurement.

Microribonucleic acids (miRNAs) have emerged as a new category of biomarkers for many human diseases like cancer, cardiovascular and neurodegenerative disorders. MicroRNAs can be detected in various body fluids including blood, urine and cerebrospinal fluid. However, the literature contains conflicting results for circulating miRNAs, which is the main barrier to using miRNAs as non-invasive biomarkers. This variability in results is largely due to differences between studies in sample processing methodology, miRNA quantification and result normalization. The purpose of this review is to describe the various preanalytical, analytical and postanalytical factors that can impact miRNA detection accuracy and to propose recommendations for the standardization of circulating miRNAs measurement.

A Retrospective Observational Study to Assess the Quality Management System in a Molecular Diagnostic Laboratory of a COVID-19 Dedicated Hospital in Delhi, India

Introduction: A molecular diagnostic laboratory is the cornerstone of Coronavirus Disease-2019 (COVID-19) disease diagnosis, as the patient’s treatment and management protocol depend on molecular results. Therefore, the laboratory conducting these tests must adhere to quality management process to increase the accuracy and validity of the generated reports. Rajiv Gandhi Super Speciality Hospital established its molecular diagnostic set-up at the beginning of the pandemic. Hence, this study aims to generate quality management data to help improve weak points. Aim: To assess the quality management system for COVID-19 diagnosis. Materials and Methods: This retrospective observational study was conducted at Rajiv Gandhi Super Speciality Hospital in Delhi, India. A total of 14,561 samples were collected over six months, from February 2021 to July 2021. Data from all samples received during this period for COVID-19 ReverseTranscriptase Polymerase Chain Reaction (RT-PCR) testing were included. Data were retrospectively collected from the electronic Laboratory Information Management System (LIMS). Quality variables were analysed over six months from July to December 2021 and classified into preanalytical, analytical, and postanalytical variables. Quality Indicators (QIs) were selected from a common model of QIs set by the International Federation of Clinical Chemistry and Laboratory Medicine. The results were presented in percentages, and descriptive statistics were analysed using Statistical Package for Social Sciences (SPSS) software. Results: During the six-month study period, the molecular laboratory received 14,561 samples. Among the preanalytical variables, sample leakage was the most common cause of sample rejection (134 samples, 0.92%), followed by the non generation of Specimen Referral Form (SRF) identification (76 samples, 0.52%), and non compliance with triple packaging (44 samples, 0.3%). Other preanalytical aspects assessed included incomplete patient identification (17 samples, 0.11%), insufficient sample quantity (12 samples, 0.08%), missing forms/samples (7 samples, 0.04%), samples in the wrong vials/ empty Viral Transport Media (VTM) tubes (5 samples, 0.03%), and incomplete LIMS entry (2 samples, 0.01%). Internal Quality Control (QC) was not obtained in 55 samples (0.37%), and two incidents of cross-contamination resulted in false-positive results. Among the postanalytical factors, 11 samples (0.07%) could not be dispatched within the stipulated time frame. Conclusion: The assessment of the quality management system revealed some areas for improvement, emphasising the importance of adhering to QC processes for the smooth operation of diagnostic laboratories, especially those involved in critical reporting. The assessment of QIs helped monitor laboratory parameters effectively.

Process improvement in automated blood cultures: Our road to better patient care

BackgroundBlood cultures (BC) are a complex multistep process susceptible to errors at multiple levels. Our study was conducted to monitor the compliance to standard operating procedures, design an intervention plan for improvement and monitor the impact of the intervention. The study design focuses on the intervention. MethodsA hospital-based prospective interventional study was carried out, monitoring various pre-analytical, analytical, and post-analytical factors in two phases. Our interventions focused on communication and training for the deficiencies noted in completeness of test request form, contamination rates, and sample loading interval. ResultsComparison between both phases showed a statistically significant improvement (p < 0.05, Chi square test) following our interventions in the completeness of test request form, contamination rates and sample loading interval. There was an improvement in the intimation of critical Gram stain from positive flagged bottles, which was not statistically significant. ConclusionOur study highlights how educational interventions can influence quality of BC. Continuous monitoring and interventions are key for quality improvement in BC processes.

A Laboratory Medicine Perspective on the Investigation of Phaeochromocytoma and Paraganglioma.

Phaeochromocytomas (PC) and sympathetic paragangliomas (PGL) are potentially malignant tumours arising from the adrenal medulla (PC) or elsewhere in the sympathetic nervous system (PGL). These tumours usually secrete catecholamines and are associated with significant morbidity and mortality, so accurate and timely diagnosis is essential. The initial diagnosis of phaeochromocytoma/paraganglioma (PPGL) is often dependent on biochemical testing. There is a range of pre-analytical, analytical and post-analytical factors influencing the analytical and diagnostic performance of biochemical tests for PPGL. Pre-analytical factors include patient preparation, sample handling and choice of test. Analytical factors include choice of methodology and the potential for analytical interference from medications and other compounds. Important factors in the post-analytical phase include provision of appropriate reference ranges, an understanding of the potential effects of various medications on metanephrine concentrations in urine and plasma and a consideration of PPGL prevalence in the patient population being tested. This article reviews these pre-analytical, analytical and post-analytical factors that must be understood in order to provide effective laboratory services for biochemical testing in the diagnosis of PPGL.

Direct oral anticoagulants (DOACs): From the laboratory point of view.

Direct oral anticoagulants (DOACs) represent a new generation of drugs that have been increasingly used in the prevention and treatment of thromboembolic states. According to the mechanism of anticoagulant action, DOACs are divided into two groups: direct inhibitors of thrombin (dabigatran) and direct inhibitors of activated factor X (FXa) (rivaroxaban, apixaban, edoxaban, betrixaban). Compared to the vitamin K antagonists, DOACs are superior in terms of onset of action, pharmacokinetic and pharmacodynamics properties and fixed daily dose without the need for routine coagulation monitoring. Despite these advantages, there are clinical conditions in which laboratory measurement of DOACs should be performed. Although DOACs have an impact on screening haemostasis assays (prothrombin time, PT; activated partial thromboplastin time, aPTT; and thrombin time, TT), these tests are not appropriate for quantifying drug levels. Therefore, specific quantitative methods (LC-MS/MS as a gold standard method for all DOACs, coagulometric and chromogenic assays for dabigatran, and chromogenic anti-Xa assays with drug-specific calibrators for inhibitors of FXa) should only be used for determination of DOACs concentration. The aim of this review is to present all aspects of laboratory assessment of DOACs, including pre-analytical, analytical and post-analytical factors in the overall testing process with a special accent on the available specific quantitative methods for measurement of DOACs in circulation.

Stability of Selected Biochemical Analytes in Serum Stored at Room Temperature for 24 Hours at Kericho County Referral Hospital, Kenya

Accurate and reliable medical laboratory test results are essential for correct patient diagnosis and management. This is however influenced by many preanalytical, analytical, and post-analytical factors. A general problem faced by most clinical laboratories is the inability to timely process all blood samples received due to overwhelming workload, reagents stock-outs, and equipment breakdown, necessitating storage which predisposes analytes to deterioration. To ensure accurate results from stored samples, the determination of the stability of the analytes under various environmental conditions and storage periods is important in informing acceptable sample handling and storage. This study was designed to experimentally observe changes and evaluate the stability of eleven biochemical analytes in serum samples from 20 randomly sampled healthy volunteers stored at room temperature over 24 hours at Kericho County Referral Hospital laboratory. 10mls of venous blood was drawn from each volunteer, serum was separated and five aliquot sets were prepared. Analysis was done on a set immediately, at 2, 4, 8, and 24 hours, to determine the concentration of the selected analytes on Human Star 100 chemistry analyser. Student pair T-test and Wilcoxon rank were used to analyse the data. Chloride, Creatinine, Glucose, Potassium, Sodium, Urea, Alkaline Phosphatase, Alanine Amino Transferase and Aspartate Amino Transferase registered stability up to 24 hours, with mean percentage differences less the respective calculated reference change value of 4.54, 35.97, 13.14, 10.89, 2.16, 32.15, 16.48, 42.25 and 42.52. Direct and total bilirubin showed stability only up to 2 and 4 hours, respectively, with mean percentage differences of -2.6 and 1.07 against respective calculated reference change values of 1.14 and 0.675 in the subsequent analysis. This study recommends immediate analysis of serum for total and direct bilirubin, while electrolytes, enzymatic analytes and other metabolic waste and substrates can be analysed within 24 hours without extra storage precautions. If testing is delayed, then effective storage including a dark room, refrigeration, or freezing, should be applied to maintain analytes stability for reliable results.

Integrating Image Analysis and Dental Radiography for Periodontal and Peri-Implant Diagnosis

The recent change in classification of periodontal and peri-implant diseases includes objective evaluation of intra-oral radiographs and quantification of bone loss for disease staging and grading. Assessment of the progression of periodontal disease requires deduction of bone loss longitudinally, and its interpretation as (1) a percentage in relation to tooth root and (2) as a function of the patient's age. Similarly, bone loss around dental implants, after accounting for initial remodeling, is central for determining diagnosis, severity, and progression of peri-implantitis. Bone gain secondary to periodontal regeneration can be measured using standardized dental radiographs and compared to baseline morphology to determine treatment success. Computational image analysis, including machine learning (ML), has the potential to develop and automate quantitative measures of tooth, implant, bone volumes, and predict disease progression. The developed algorithms need to be standardized while considering pre-analytic, analytic, and post-analytic factors for successful translation to clinic. This review will introduce image analysis and machine learning in the context of dental radiography, and expand on the potential for integration of image analysis for assisted diagnosis of periodontitis and peri-implantitis.

What Every Neuropathologist Needs to Know: Practical Aspects and Pitfalls in Molecular Diagnosis of Brain Tumors.

Molecular testing has become part of the routine diagnostic workup of brain tumors after the implementation of integrated histomolecular diagnoses in the 2016 WHO classification update. It is important for every neuropathologist to be aware of practical preanalytical, analytical, and postanalytical factors that impact the performance and interpretation of molecular tests. Prior to testing, optimizing tumor purity and tumor amount increases the ability of the molecular test to detect the genetic alteration of interest. Recognizing basic molecular testing platform analytical characteristics allows selection of the optimal platform for each clinicopathological scenario. Finally, postanalytical considerations to properly interpret molecular test results include understanding the clinical significance of the detected genetic alteration, recognizing that detected clinically significant genetic alterations are occasionally germline constitutional rather than somatic tumor-specific, and being cognizant that recommended and commonly used genetic nomenclature may differ. Potential pitfalls in brain tumor molecular diagnosis are also discussed.

Blood Serum Stability Limit and Maximum Storage Time of Bovine Samples

Background: Measuring metabolic parameters in the blood has been an indispensable tool for assessing the productive and health status of dairy cows for more than 100 years. The values of laboratory parameters depend on various preanalytical, analytical and postanalytical factors. The most important preanalytical factors are sample transport time and temperature, hemolysis, anticoagulant type, and sample volume.Preanalytical factors can lead to reduced stability of the analyte in the sample, which changes their concentration. Loss of stability changes the time of storage and manipulation of the sample, which determines the criteria for its acceptance or rejection. The two stability indicators are stability limit and maximum permissible instability. A stability limit (SL) is defined as the period of time in which a property variation does not exceed a maximum permissible instability (MPI). The aim of this study was to determine the SL and MPI for each analyte in the blood serum of cows and to determine whether SL differs in the function of the presence of preanalytical errors in the blood sample.Materials, Methods &amp; Results: Three hundred samples of dairy cow origin in different periods of lactation participated in this research. They were classified into 6 groups of 50 samples: according to the time from sampling to processing in the laboratory (0-4 h, 4-8 h and over 8 h; all transported on dry ice, protected from environmental factors, without preanalytical errors) and according to the presence of preanalytical errors (group with hemolysis, a group transported at ambient temperature and a group with a small sample volume). Each sample was aliquoted in two portions. One portion was left at +4°C and tested once a day for 6 days of sample storage, and the second portion, placed at -20 °C, was tested once a month for 6 months. The MPI had a value ranging from 1.55 to 8.4. Metabolic profile analytes with lower MPI values (1.51-3.22) were albumin (ALB), total protein (TPROT), UREA, glucose (GLU), calcium (Ca), and phosphorus (P). Higher MPI values (5.1-8.3) were found for nonesterified fatty acids (NEFA), beta-hydroxybutirate (BHB), cholesterol (CHOL), triglycerides (TGC), total bilirubin (TBIL) and aspartat aminotransferase (AST). For most parameters, we can conclude that their PD% changed faster in storage conditions at +4 °C compared to the regime of -20 °C. The largest number of biochemical analytes in bovine blood serum shows preserved stability in the first 6 days at +4°C or 6 months at -20°C if transported to the laboratory within 8 h after sampling in ideal conditions and without the action of preanalytical errors. Prolonged transport under ideal conditions or the existence of preanalytical errors such as transport at room temperature, hemolysis or small sample volume shorten the stability of the ALB, NEFA, GLU, UREA and P. Concentration of all analytesdecreasesduring the stability test except for UREA, NEFA, BHB and for CHOL and TGC in some groups. Variations in parameters such as BHB, NEFA, TBIL, AST, and Ca have shown potential clinical significance. At storage conditions at +4°C, clinically significant variations at at least one measurement point were found for AST (7.5% of samples), BHB (6.1% of samples), NEFA (9.9% of samples) and for TBIL (in 7% of samples).Discussion: This study can help define acceptable delay times and storage conditions for bovine blood samples, which is of great importance because in working with farm animals it is often not possible to take samples in a short time and deliver them to the laboratory, and samples are often burdened with certain preanalytical errors with limited possibilities of re-sampling.

Evaluation of quality assurance in the cytopathology laboratory of a tertiary care hospital in Eastern India

Background: In this era of evidence-based medicine, clinical laboratories play a critical role in patient diagnosis and management. Aims: The present study aims to study the quality assurance in the cytopathology laboratory of a tertiary care hospital in the Eastern region of India. Materials and Methods: An observational, retrospective, and analytic study for 1 year was conducted. The sample size was 600. Simple random samples were selected including pleural fluids, ascitic fluids, cerebrospinal fluids, cervical cytology Pap smears, fine needle aspiration (FNA) cytology, and guided FNA samples. Results: Maintenance of authentication of reports and ISO accreditation showed no deficiency, whereas report generation, dispatch, and documentation of duplicate reports showed the highest deficiency (593, 98.8%) in maintaining quality assurance. Incomplete requisition was the most common cause of registration failure (3, 42.8%), whereas samples sent in wrong vials was the most common cause of sample collection failure (3, 37.5%). The presence of artifacts was the major factor affecting smearing technique (3, 50%). Lack of compliance to standardized protocol in manual staining and mechanical factors of automated strainers affected the staining quality (3, 37.5% each). Power cut and lack of adequate UPS backup affected the productivity of equipment mostly (3, 50%). Technical issues were the major factor affecting turnaround time (3, 50%). Lack of manpower at the report dispatch counter and logistics affected report generation and dispatch (2, 33.3% each). Randomly selected reports were crosschecked with histology and prediction accuracy measures were calculated. Conclusion: The preanalytical, analytical, and postanalytical factors have to be maintained adequately for ensuring quality assurance.

Inconsistent Intersample ALK FISH Results in Patients with Lung Cancer: Analysis of Potential Causes.

ALK FISH analyses of multiple specimens occasionally yield inconsistent intersample results in lung cancer patients, posing clinical challenges requiring intensive analysis of all potential causative pre- and post- analytic factors. In this study, 19 patients (8M/11F) with inconsistent intersample ALK FISH results were analyzed, representing 4.9% of patients assessed ≥ twice in our institution. Fifteen patients received ALK tyrosine kinase inhibitor(s) (TKIs). Nine patients died, and ten were alive for 8 to 74-month follow-ups (median, 40 months). Through strict and stringent laboratory and case-review policies, all postanalytic factors were excluded. Correlating clinical information, ALK results obtained by RNA sequencing (RNA-seq) and other concurrent tests, several pre-analytic factors were determined. A suboptimal specimen was likely the cause in three patients, supported by the failure of one or more concurrent tests or discrepant results between FISH and RNA-seq. ALK inhibition by TKIs might have been responsible for the change of ALK status from positive to negative in eight patients. Other potential explanations include the existence of multiple primary lung cancer lesions, tumor heterogeneity, and the clonal evolution of tumor cells, related or not to ALK TKI therapy. This study is helpful for both pathologists and clinicians encountering inconsistent and/or discrepant intersample results.

Molecular Diagnostics in Non-Small Cell Lung Carcinoma.

Current clinical practice guidelines recognize EGFR, BRAF, ALK, and ROS1 as essential molecular biomarkers, and a host of other genetic alterations as emerging biomarkers for non-small cell lung carcinoma patients. The available approaches to detecting relevant alterations in these genes are diverse and often complementary. Laboratories have increasingly migrated away from a "single-gene test" approach, embracing assays that incorporate panels of genes capable of detecting a diverse set of alterations. The adoption of next generation sequencing (NGS) techniques has driven this shift; however, the approach to incorporation of NGS varies greatly between practices. Choice of molecular diagnostics assay, be it single-gene or NGS-based panel, will be driven by cost, urgency, clinical and laboratory focus, and professional considerations. Preanalytic factors including operator expertise, sample type and choice of fixative, and postanalytic factors including informatics pipeline and approaches to variant reporting have a significant impact on the quality of molecular diagnostics results. There is no real "one-size-fits-all" test for genomic profiling for lung cancer; clinicians and laboratorians must be prepared to offer a diverse set of assays in order to address turnaround time requirements and optimize detection of critical but difficult-to-detect tumor alterations such as gene fusions.

Key questions about the future of laboratory medicine in the next decade of the 21st century: A report from the IFCC-Emerging Technologies Division

This review advances the discussion about the future of laboratory medicine in the 2020s. In five major topic areas: 1. the “big picture” of healthcare; 2. pre-analytical factors; 3. Analytical factors; 4. post-analytical factors; and 5. relationships, which explores a next decade perspective on laboratory medicine and the likely impact of the predicted changes by means of a number of carefully focused questions that draw upon predictions made since 2013. The “big picture” of healthcare explores the effects of changing patient populations, the brain-to-brain loop, direct access testing, robots and total laboratory automation, and green technologies and sustainability. The pre-analytical section considers the role of different sample types, drones, and biobanks. The analytical section examines advances in point-of-care testing, mass spectrometry, genomics, gene and immunotherapy, 3D-printing, and total laboratory quality. The post-analytical section discusses the value of laboratory medicine, the emerging role of artificial intelligence, the management and interpretation of omics data, and common reference intervals and decision limits. Finally, the relationships section explores the role of laboratory medicine scientific societies, the educational needs of laboratory professionals, communication, the relationship between laboratory professionals and clinicians, laboratory medicine financing, and the anticipated economic opportunities and outcomes in the 2020's.

Prostate cancer screening: guidelines review and laboratory issues.

Background Prostate-specific antigen (PSA) remains as the most used biomarker in the detection of early prostate cancer (PCa). Clinical practice guidelines (CPGs) are produced to facilitate incorporation of evidence into clinical practice. This is particularly useful when PCa screening remains controversial and guidelines diverge among different medical institutions, although opportunistic screening is not recommended. Methods We performed a systematic review of guidelines about PCa screening using PSA. Guidelines published since 2008 were included in this study. The most updated version of these CPGs was used for the evaluation. Results Twenty-two guidelines were selected for review. In 59% of these guidelines, recommendations were graded according to level of evidence (n = 13), but only 18% of the guidelines provided clear algorithms (n = 4). Each CPG was assessed using a checklist of laboratory issues, including pre-analytical, analytical, and post-analytical factors. We found that laboratory medicine specialists participate in 9% of the guidelines reviewed (n = 2) and laboratory issues were frequently omitted. We remarked that information concerning the consequences of World Health Organization (WHO) standard in PSA testing was considered by only two of 22 CPGs evaluated in this study. Conclusions We concluded that the quality of PCa early detection guidelines could be improved properly considering the laboratory issues in their development.

Immunocytochemistry for predictive biomarker testing in lung cancer cytology.

With an escalating number of predictive biomarkers emerging in non-small cell lung carcinoma (NSCLC), immunohistochemistry (IHC) is being used as a rapid and cost-effective tool for the screening and detection of many of these markers. In particular, robust IHC assays performed on formalin-fixed, paraffin-embedded (FFPE) tumor tissue are widely used as surrogate markers for ALK and ROS1 rearrangements and for detecting programmed death ligand 1 (PD-L1) expression in patients with advanced NSCLC; in addition, they have become essential for treatment decisions. Cytology samples represent the only source of tumor in a significant proportion of patients with inoperable NSCLC, and there is increasing demand for predictive biomarker testing on them. However, the wide variation in the types of cytology samples and their preparatory methods, the use of alcohol-based fixatives that interfere with immunochemistry results, the difficulty in procurement of cytology-specific controls, and the uncertainty regarding test validity have resulted in underutilization of cytology material for predictive immunocytochemistry (ICC), and most cytopathologists limit such testing to FFPE cell blocks (CBs). The purpose of this review is to: 1) analyze various preanalytical, analytical, and postanalytical factors influencing ICC results; 2) discuss measures for validation of ICC protocols; and 3) summarize published data on predictive ICC for ALK, ROS1, EGFR gene alterations and PD-L1 expression on lung cancer cytology. Based on our experience and from a review of the literature, we conclude that cytology specimens are in principal suitable for predictive ICC, but proper optimization and rigorous quality control for high-quality staining are essential, particularly for non-CB preparations.

Pre- and Post-analytical Factors in Biomarker Discovery.

The translation of promising biomarkers, which were identified in biomarker discovery experiments, to clinical assays is one of the key challenges in present-day proteomics research. Many so-called "biomarker candidates" fail to progress beyond the discovery phase, and much emphasis is placed on pre- and post-analytical variability in an attempt to provide explanations for this bottleneck in the biomarker development pipeline. With respect to such variability, there is a large number of pre- and post-analytical factors which may impact the outcomes of proteomics experiments and thus necessitate tight control. This chapter highlights some of these factors and provides guidance for addressing them on the basis of examples from previously published proteomics studies.

Hormone receptor (ER, PR, HER2/neu) status and proliferation index marker (Ki-67) in breast cancers: Their onco-pathological correlation, shortcomings and future trends

Estrogen receptor (ER) and progesterone receptor (PR) are hormone receptors found on breast cells that pick up hormone signals resulting in cell growth. Similarly, positive human epidermal growth factor receptor-2 (HER2/neu) status of the breast carcinoma means that HER2/neu gene is making too many HER2/neu proteins, which acts as receptors on the cell surface and helps the cells to grow and divide. Hormone receptor studies such as ER, PR, and HER2/neu are routinely done in breast carcinoma. It not only helps in the prognosis of the tumor but also helps in deciding its treatment. The goal of doing this receptor status is to provide right treatment to the right patient. This hormone receptor status is graded using Allred scoring and grading system. Depending on the hormone status, breast carcinomas can be divided into a number of different categories ranging from triple positive through triple negative. Another marker of proliferation (Ki-67) is also being used which is a proliferation index marker. This scoring system has its own limitation and shortcomings, which depends on a lot of pre- and post-analytical factors. Certain new techniques such as genomic assays, PAM50, and HALO screening test are being used nowadays for breast cancer detection.

Obstacles to precision oncology: confronting current factors affecting the successful introduction of biomarkers to the clinic.

Tailoring treatment strategies to individual patients requires the availability of reliable biomarkers. Despite important investment in biomarker research, few examples of successful biomarker-drug co-development are currently seen in clinical practice. The validity of a biomarker measurement may be affected by different pre-analytical, analytical and post-analytical factors. The lack of control or oversight of any of these factors may ultimately lead to failure in translating a promising research finding into clinical practice. In the present review, we put into perspective some of the obstacles to "precision" oncology, focusing on the technical and biological hurdles that may affect the validity of a biomarker result and, ultimately, the likelihood of a new targeted agent to reach the clinic. Biomarker application in precision oncology must consider the evolution of neoplastic disease, evaluate strengths and limitations of the platform used for the determination, and efficiently address specimen type and handling issues. In-depth analytical validation of a new biomarker test that includes evaluation of target stability should be performed before the test is used in clinical samples. More efficient sampling and use of high-sensitivity methodologies may overcome the influence of tumor heterogeneity on biomarker measurement. Clinical trials with biomarker endpoints may only be successful when multidisciplinary academic study teams are involved and results meet the highest quality standards.