1.1. Introduction

1.2. Overview of established uses

1.3. Recent Progress

1.3.1. Monoclonal FLC studies

1.3.2. Polyclonal FLC studies

1.3.3. HLC studies

1.3.4. New guidelines

2.1. The identification of Bence Jones protein

2.2. The identification of serum monoclonal proteins

​2.3. Free light chain assays

2.4. Immunoglobulin heavy/light chain assays

3.1. Immunoglobulin structure

3.2. Immunoglobulin diversity

​3.3. Isotypic and allotypic variation of light chain constant domains

3.4. Immunoglobulin and FLC production

3.5. Clearance and metabolism

3.5.1. Half-life of sFLCs

3.5.2. Renal clearance of FLCs

3.5.3. Half-life of IgG, IgA and IgM

4.1 Introduction

4.2 Detection and quantification of serum monoclonal proteins

4.2.1. Serum protein electrophoresis

4.2.2. Capillary zone electrophoresis

4.2.3. Diagnostic sensitivity of SPE and CZE compared with other laboratory techniques

4.2.4. Serum free light chain analysis

4.2.5. Hevylite immunoassays

4.3. Typing of serum monoclonal proteins

4.3.1. Immunofixation electrophoresis

4.3.2. Immunosubtraction

4.4. Other serum assays

4.4.1. Total immunoglobulin assays

4.4.2. Total κ/λ assays

4.5. Detection and quantification of urine monoclonal proteins

4.5.1. Urine protein electrophoresis

4.5.2. Urine capillary zone electrophoresis

4.5.3. Urine free light chain assays

5.1. Assay overview

5.2. Polyclonal antisera versus monoclonal antibodies

5.3. Antisera specificity testing

5.3.1. Immunoelectrophoresis

5.3.2. Western blot analysis

5.3.3. Haemagglutination assays

5.3.4. Nephelometry

5.4. Accuracy and standardisation

5.5. Maintaining batch-to-batch consistency of polyclonal antisera-based latex reagents

5.6. Overview of Freelite assay validation

5.7. Overview of Freelite kit manufacture

5.8. Immunoassay development on different platforms

6.1. Freelite® serum reference intervals

6.1.1. Ethnic influences

6.2 Borderline Freelite results

6.3 Freelite renal reference intervals

6.4 Freelite urine reference intervals

7.1. Implementation of Freelite assays

7.1.1. Choice of instrument

7.1.2. Reporting units

7.1.3. Choice of sample

7.1.4. Sample and reagent stability

7.1.5. Changing reagent lot or instrument

7.2. Interpretation of Freelite assays

7.2.1. Normal reference intervals

7.2.2. Terminology

7.2.3. The FLC dot plot

7.2.4. Result interpretation

7.2.5. sFLCs and intact immunoglobulins are independent tumour markers

7.2.6. Biological variation

7.3. Sample redilution

7.4. Sample linearity

7.4.1. Managing non-linearity

7.5. Antigen excess

7.5.1. Instruments with automated antigen excess checking

7.5.2. Instruments without automated antigen excess checking

7.5.3. Incidence of antigen excess

7.6. Polymerisation

7.7. Discrepant results

7.7.1. Monoclonal FLCs in urine, normal sFLCs

7.7.2. Monoclonal FLCs detectable by sIFE but undetectable by sFLC immunoassay

7.7.3. No monoclonal proteins detectable by any routine laboratory method

7.8. Biclonal gammopathies

8.1. Introduction

8.2. Overview of commercial FLC assays

8.3. Monoclonal vs. polyclonal antisera

8.3.1. Monoclonal antibody production

8.3.2. Polyclonal antisera production

8.3.3. Requirements for anti-FLC antibodies for use in FLC immunoassays

8.4. Analytical performance of monoclonal and polyclonal antibody-based FLC assays

8.4.1. Calibration

8.4.2. Precision

8.4.3. Linearity

8.4.4. Antigen excess

8.4.5. Sample redilution

8.5. Reference intervals

8.5.1. Normal reference intervals

8.5.2. Renal reference interval

8.6. Clinical performance

8.6.1. Comparison of absolute values

8.6.2. Diagnostic performance in MM

8.6.3. Rationale for the diagnoses of LCMM missed by monoclonal antibody-based FLC assays

8.6.4. Monitoring MM

8.6.5. Diagnostic performance in cast nephropathy

8.6.6. Diagnostic performance in AL amyloidosis

8.6.7. Monitoring AL amyloidosis

8.7. Compliance with guidelines

8.8. Conclusion

9.1. Assay overview

9.2. Polyclonal antisera production

9.3. Antisera specificity testing

9.4. Accuracy and standardisation

9.4.1. Primary standards and internal reference standards

9.4.2. Kit calibrators and controls

9.4.3. Calibration curves

9.4.4. Correlation with total immunoglobulin measurements

9.5. Maintaining batch-to-batch consistency of polyclonal antisera-based reagents

9.6. Overview of Hevylite assay validation

9.7. Overview of Hevylite kit manufacture

9.8. Immunoassay development on different platforms

10.1. Introduction

10.2. Standardisation of immunoglobulin assays

10.3. Hevylite standardisation

10.4. Hevylite reference intervals

10.4.1. Binding Site Hevylite reference intervals

10.4.2. Other Hevylite reference intervals

10.5. Choice of reference interval

11.1. Implementation of Hevylite assays

11.1.1. Choice of instrument

11.1.2. Reporting units

11.1.3. Choice of sample

11.1.4. Sample and reagent stability

11.1.5. Changing batch of reagent or instrument

11.2. Interpretation of Hevylite assays

11.2.1. Normal reference intervals

11.2.2. Terminology

11.2.3. Result interpretation

11.2.4. The HLC dot plot

11.2.5. Freelite and Hevylite are independent tumour markers

11.2.6. Biological variation

11.3. Linearity

11.3.1. Managing non-linearity

11.4. Antigen excess

11.5. Comparison of Hevylite results with other immunoglobulin tests

11.5.1. Comparison of Hevylite and total immunoglobulin measurements

11.5.2. Comparison of Hevylite and immmunoglobulin measurements by SPE

11.5.3. Comparison of Hevylite and immunofixation electrophoresis

12.1. Introduction

12.2. Multiple myeloma and related malignant disorders

12.3. MGUS and SMM

12.4. Improving our understanding of disease pathogenesis and response to therapy

13.1. MGUS definition and frequency

13.1.1. Light Chain MGUS

13.2. Risk factors for MGUS progression

13.2.1. Prognostic value of serum FLCs in MGUS

13.2.2. Prognostic value of Hevylite in MGUS

13.3. MGUS as the precursor condition for MM and related disorders

13.3.1. MGUS consistently precedes MM

13.3.2. Risk of MGUS progression to MM may change

13.3.3. MGUS is associated with increased mortality

13.3.4. Prior knowledge of MGUS improves multiple myeloma survival

14.1. Introduction

14.2. Monoclonal sFLCs and SMM progression

14.3. The prognostic value of HLC analysis at baseline

14.4. The prognostic value of changes in monoclonal protein concentration

15.1. Diagnosis of light chain multiple myeloma

15.2. Monitoring light chain multiple myeloma

15.3. Prognostic value of the sFLC response in light chain multiple myeloma

16.1. Introduction

16.2. Diagnosis of nonsecretory multiple myeloma

16.3. Monitoring nonsecretory multiple myeloma

17.1. Introduction

17.2. Free light chains at diagnosis

17.3. International guidelines for the quantification of monoclonal immunoglobulins in IIMM

17.4. Limitations of electrophoresis

17.5. Limitations of total immunoglobulin measurements

17.6. Immunoglobulin HLC immunoassays (Hevylite) at diagnosis

18.1. Introduction

18.2. Current guidelines for monitoring IIMM

18.2.1. Detection of free light chain escape

18.2.2. Definition of a stringent complete response

18.3. Other uses of sFLC analysis in IIMM response assessment

18.3.1. Rapid assessment of response

18.3.2. Prediction of overall response

18.3.3. Early detection of ineffective therapy

18.3.4. Early detection of disease relapse

18.3.5. Monitoring patients treated with monoclonal antibody-based therapies

18.4. Monitoring IIMM patients using HLC assays

18.4.1. HLC assays are quantitative and non-subjective

18.4.2. HLC assays to monitor oligosecretory patients

18.4.3. HLC assays in MRD assessment

18.4.4. HLC assays improve detection of relapse

18.4.5. Discrepancies between HLC and IFE during follow-up

19.1. Introduction

19.2. Clonal populations in multiple myeloma

19.3. Clonal changes and clonal escape in multiple myeloma

20.1. Introduction

20.2. sFLCs at diagnosis

20.2.1. sFLCs combined with the ISS

20.2.2. Association between sFLCs and other prognostic markers

20.3. sFLCs during response assessment

20.3.1. Normalisation of the sFLC ratio and importance of a sCR

20.3.2. Early sFLC response predicts outcome

20.3.3. Prognostic implications of relapse with FLCs

20.4. HLC analysis at diagnosis

20.5. HLC analysis during response assessment

20.6. Prognostic value of combining sFLC and HLC measurements

21.1. Introduction

21.2. Monoclonal proteins in solitary plasmacytoma

21.3. Prognostic factors in solitary plasmacytoma

21.4. Guideline recommendations

22.1. Introduction

22.2. Diagnosis and monitoring of plasma cell leukaemia using sFLCs

23.1. Introduction

23.2. Screening panels for the detection of monoclonal gammopathies

23.3. Incorporation of sFLC analysis into routine screening for monoclonal gammopathies

23.3.1 Screening for monoclonal gammopathy in patients presenting with renal dysfunction

23.3.2 Interpretation of borderline sFLC ratios

23.4. The sensitivity of abnormal sFLC ratios for Bence Jones proteinuria

23.5. Issues with urine compliance

23.6. Organisational and cost implications of screening algorithms

24.1. Introduction

24.2. Renal threshold for FLC excretion

24.3. Problems measuring urine samples

24.4. Urine compliance

24.5. Urine FLC immunoassays

24.6. Clinical benefits of sFLC analysis

24.7. Elimination of urine studies when screening for monoclonal gammopathies

24.8. Comparison of sFLCs and urinalysis for monitoring patients

24.9. Discrepant serum and urine results

24.10. Organisational cost savings and other benefits of sFLC analysis

24.11. Conclusions

25.1. Introduction

25.2. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma

25.2.1. Definition of multiple myeloma

25.2.2. Definition of smouldering multiple myeloma

25.2.3. Definition of monoclonal gammopathy of undetermined significance

25.3. International Myeloma Working Group guidelines

25.3.1. Guidelines for serum free light chain analysis in multiple myeloma and related disorders (2009)

25.3.2. Guidelines for monoclonal gammopathy of undetermined significance and smouldering multiple myeloma (2010)

25.3.3. Guidelines for standard investigative work-up of patients with suspected multiple myeloma (2011)

25.3.4. Guidelines for risk stratification in multiple myeloma (2011)

25.3.5. Consensus criteria for response and minimal residual disease assessment in multiple myeloma (2016)

25.3.6. Recommendations for global myeloma care (2013)

25.3.7. Recommendations for the diagnosis and management of myeloma-related renal impairment (2016)

25.4. European Society of Medical Oncology: clinical practice guidelines for diagnosis, treatment and follow-up of multiple myeloma (2017)

25.5. UK Myeloma Forum and Nordic Myeloma Study Group: guidelines for the investigation of newly detected monoclonal proteins and management of monoclonal gammopathy of undetermined significance (2009)

25.6. British Committee for Standards in Haematology Guidelines (2014)

25.7. National Institute for Health and Care Excellence Guideline 35: myeloma diagnosis and management (2016)

25.8. NCCN Clinical Practice Guidelines In Oncology (NCCN Guidelines®) for Multiple Myeloma V.2.2019

25.9. Management of multiple myeloma in Asia: resource-stratified guidelines

26.1. Introduction

26.2. Renal clearance of free light chains

26.3. Renal impairment and free light chains

26.4. Nephrotoxicity of monoclonal FLCs

26.4.1. Monoclonal gammopathy of renal significance

27.1. Renal impairment in multiple myeloma

27.2. Screening for multiple myeloma in patients with unexplained AKI

27.3. Cast nephropathy

27.4. Light chain removal strategies in cast nephropathy

27.4.1. Plasma exchange

27.4.2. High cut-off haemodialysis

27.4.3. Haemodialysis and adsorption

27.5. Renal recovery is associated with reductions in FLCs

28.1. Introduction

28.2. Diagnosis of AL amyloidosis

28.2.1 Localised amyloid disease

28.3. Guidelines for the diagnosis of AL amyloidosis

28.3.1. International Myeloma Working Group (2009)

28.3.2. British Committee for Standards in Haematology (2015)

28.3.3 NCCN Clinical Practice Guidelines In Oncology (NCCN Guidelines®) for Systemic Light Chain Amyloidosis V.1.2019

28.4. Prognostic value of sFLCs at diagnosis

28.5 AL amyloidosis patients with distinct clinical features

28.5.1 Cardiac amyloidosis

28.5.2 Patients with low amyloidogenic FLCs

28.5.3 IgM AL amyloidosis

28.6. Monitoring patients with AL amyloidosis

28.7. Guidelines for monitoring AL amyloidosis

28.7.1. International Myeloma Working Group (2009)

28.7.2. Consensus guidelines for the conduct and reporting of clinical trials in systemic light-chain amyloidosis (2012)

28.7.3. British Committee for Standards in Haematology (2015)

28.7.4. NCCN Clinical Practice Guidelines In Oncology (NCCN Guidelines®) for Systemic Light Chain Amyloidosis V.1.2019

28.8. Prognostic value of sFLC response

28.8.1. sFLC response predicting cardiac outcomes

28.8.2. sFLC response and renal outcome

28.9. SAP scintigraphy and sFLCs

28.10. Hevylite in AL amyloidosis

29.1. Introduction

29.2. sFLC assays support a diagnosis of LCDD

29.3. Monitoring LCDD using sFLC assays

30.1. Introduction

30.2. sFLCs in lymphoid malignancies

30.3. Hevylite in lymphoid malignancies

30.4. sFLCs as a biomarker of immune stimulation and inflammation

30.5. Cerebrospinal fluid FLCs and multiple sclerosis

30.6. sFLCs as a marker of mortality

31.1. Introduction

31.2. Hodgkin lymphoma

31.3. Non-Hodgkin lymphoma: diffuse large B-cell lymphoma

31.3.1. sFLCs and HLC in DLBCL

31.3.2. Prognostic value of sFLCs and HLCs in DLBCL

31.3.3. Use of sFLCs for monitoring DLBCL

31.4. Non-Hodgkin lymphoma: mantle cell lymphoma

32.1. Introduction

32.2. IgM quantitation by routine laboratory tests

32.3. sFLCs in Waldenström's macroglobulinaemia

32.3.1. sFLCs and WM diagnosis

32.3.2. Monitoring WM using sFLCs

32.3.3. sFLC and WM prognosis

32.3.4. Guidelines for sFLC assessment in WM

32.4. IgM HLC in Waldenström's macroglobulinaemia

32.4.1. IgM HLC and WM diagnosis

32.4.2. Monitoring WM using IgM HLC

32.4.3. IgM HLC and WM prognosis

32.5. Use of sFLC and HLC analysis in IgM MGUS and asymptomatic WM

33.1. Introduction

33.2. Monoclonal and polyclonal sFLCs in CLL

33.3. Prognostic value of sFLCs at baseline

33.4. Prognostic value of combined FLC measurements

33.5. Monitoring CLL with sFLCs

34.1. Introduction

34.2. Cryoglobulinaemia

34.3. Heavy chain diseases

34.4. POEMS syndrome

35.1. Introduction

35.2. Chronic kidney disease

35.3. Cardiovascular disease

35.4. Rheumatic diseases

35.4.1. Systemic lupus erythematosus

35.4.2. Primary Sjögren’s syndrome

35.4.3. Rheumatoid arthritis

35.4.4. Systemic sclerosis

35.5. Diabetes mellitus

35.6. Human immunodeficiency virus

35.7. Allergies

35.8. Other diseases

35.8.1. Respiratory disease

35.8.2. Hepatitis C virus and liver disease

35.8.3. Renal transplantation

35.8.4. Post-transplant lymphoproliferative disorder

35.8.5. IgG4-related disease

35.9. FLCs as bioactive molecules in inflammatory diseases

35.10. General population studies

35.11. Conclusions

36.1. Introduction

36.1.1. Multiple sclerosis and intrathecal immunoglobulin synthesis

36.2. CSF FLCs as a marker of intrathecal immunoglobulin synthesis

36.3. Prognostic significance of CSF FLCs

36.4. Other applications of CSF FLC measurements

37.1. Overview

37.2. The Binding Site Optilite

37.2.1. Overview of Freelite and Hevylite assays on the Optilite

37.2.2. Freelite and Hevylite Precision on the Optilite

37.2.3. Freelite and Hevylite antigen excess detection on the Optilite

37.3. The Binding Site SPAPLUS

37.3.1. Overview of Freelite and Hevylite assays on the SPAPLUS

37.3.2. Freelite and Hevylite Precision on the SPAPLUS

37.3.3. Freelite and Hevylite antigen excess detection on the SPAPLUS

37.4. Other analytical platforms

38.1. Introduction

38.2. The Binding Site schemes

38.2.1. QA003

38.2.2. QA003.H

38.3. United Kingdom National External Quality Assessment Service scheme

38.4. College of American Pathologists scheme

38.5. Randox International Quality Assessment scheme

38.6. German Institute for Standardisation scheme

39.1 Freelite

40.1. Disclaimer

40.2. Contact information