Assay Migration Studies for 
 
In Vitro Diagnostic Devices
  
 
Guidance for Industry and FDA 

Staff
  
 
Document  issued  on:  April 25,  2013  
 
The  draft  of  this document  was issued  on  January  5,  2009.  
 
For questions regarding this document contact  Sally Hojvat, PhD, CDRH/OIR/DMD, 
by phone at  (301)  796-5455, or by email at  sally.hojvat@fda.hhs.gov  or Marina V. 
Kondratovich, PhD, CDRH/OIR  by phone at  (301)  796-6036  or by email at  
marina.kondratovich@fda.hhs.gov.   For questions relating to devices regulated by 
CBER, contact  the Office of  Communications, Outreach and Development, CBER at  
301-827-1800 or 800-835-4709.   
  
 
U.S. Department of Health and Human Services  
Food and Drug Administration  
Center for Devices and Radiological Health  
Office of In Vitro Diagnostics  and Radiological Health  
Center for Biologics Evaluation and Research  
  Contains Nonbinding Recommendations  
 
                                                  
               Preface  
 
Public Comment 
 
You may submit written comments and suggestions at any time for Agency consideration to 
the Division of Dockets Management, Food and Drug Administration, 5630 Fishers Lane, rm. 
1061, (HFA-305), Rockville, MD, 20852. Submit electronic comments to 
http://www.regulations.gov.  Identify all comments with the docket number FDA-2008-N
0642. Comments may not be acted upon by the Agency until the document is next revised or  
updated.  
Additional Copies  
Additional copies are available from the Internet.  You may also send an email request to 
dsmica@fda.hhs.gov  to receive an electronic copy of the guidance, or send a FAX request to 
301-847-8149 to receive a hard copy.  Please use the document number  1660  to identify the 
guidance you are requesting.    
Additional  copies  of  this  guidance  document  are  also  available  from  the  Center  for  Biologics  
Evaluation  and  Research  (CBER)  by  written  request,  Office  of  Communication,  Outreach  and 
Development  (HFM-40),  1401  Rockville  Pike,  Suite  200N,  Rockville,  MD  20852-1448,  by 
telephone,  1-800-835-4709  or  301-827-1800,  by  email,   ocod@fda.hhs.gov,  or  from  the 
Internet  at  
http://www.fda.gov/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/G 
uidances/General/default.htm. 
  2   Contains Nonbinding Recommendations  
 
Table  of  Contents 
 
I.   INTRODUCTION  ................................................................................................................................... 1
  
II.   BACKGROUND  ...................................................................................................................................... 2
  
III.   SCOPE  ...................................................................................................................................................... 3
  
IV.   CRITICAL  CONSIDERATIONS  FOR  DETERMINING  WHETHER  THE  MIGRATION
  
STUDIES  PARADIGM  MAY  APPLY  TO  A  PARTICULAR  DEVICE ........................................................ 4
  
V.   ADDITIONAL  CONSIDERATIONS  .................................................................................................... 4
  
VI.   ASSAY  MIGRATION  STUDIES ........................................................................................................... 6
  
A.   MIGRATION  STUDIES FOR  QUALITATIVE ASSAYS  ................................................................................ 6
  
1.	   Analytical  Studies  for  Qualitative Assays  ............................................................................................. 6
  
a)   Performance  at  Low Analyte  Levels  ...................................................................................................................  6
  
b)   Precision  .............................................................................................................................................................  7
  
(i)   Composition of Precision Panel ......................................................................................................................  7
  
(a)  When  non-diseased subject  samples  have  a detectable  amount  of analyte. ................................................  7
  
(b)  When  non-diseased subject  samples  have  a true  zero analyte  concentration. .........................................  10
  
(c) When  an  assay  with  a numeric  value  produces  an  equivocal  result  and/or  has  a re-test  zone.  ...............  12 
 
(ii)   Within-Laboratory  Precision Study  .........................................................................................................  12
  
(iii)   Reproducibility  Study  ..............................................................................................................................  13
  
2.	   Comparison  Studies for Qualitative Assays ........................................................................................ 14
  
a)   Comparison Panels ...........................................................................................................................................  14 
 
b)   Comparison Study  Design .................................................................................................................................  15 
 
3.	   Statistical  Analysis  of  Data .................................................................................................................. 15
  
a)   Within-Laboratory  Precision Study  ..................................................................................................................  16
  
b)   Reproducibility  Study ........................................................................................................................................  16
  
c)   Comparison Panels ...........................................................................................................................................  17 
 
4.   Acceptance Criteria  for  Qualitative Assay Migration  Studies  ........................................................... 18
  
B.   MIGRATION  STUDIES FOR  QUANTITATIVE ASSAYS ............................................................................ 19
  
1.	   Analytical  Studies  for  Quantitative Assays  ......................................................................................... 19
  
a)   Performance  at  Low Analyte  Levels  .................................................................................................................  19
  
b)   Precision  ...........................................................................................................................................................  20
  
(i)   Composition of Precision Panel ....................................................................................................................  20
  
(ii)   Within-Laboratory  Precision Study  .........................................................................................................  21
  
(iii)   Reproducibility  Study  ..............................................................................................................................  22
  
c)   Linearity  Study ..................................................................................................................................................  22
  
2.	   Comparison  Studies ............................................................................................................................. 22
  
a)   Comparison Panels ...........................................................................................................................................  23 
 
b)   Comparison Study  Design .................................................................................................................................  23 
 
3.	   Statistical  Analysis  of  Data .................................................................................................................. 23
  
a)   Within-Laboratory  Precision Study  ..................................................................................................................  24
  
b)   Reproducibility  Study ........................................................................................................................................  24
  
c)   Comparison Panels ...........................................................................................................................................  25 
 
4.   Acceptance Criteria  for  Quantitative Assay Migration  Studies  ......................................................... 26
  
C.   MIGRATION  STUDIES FOR  SEMI-QUANTITATIVE ASSAYS .................................................................. 27
  
D.   MIGRATION  STUDIES FOR  POINT OF  CARE (POC)  ASSAYS ............................................................... 27
  
VII.   OTHER  STUDIES ................................................................................................................................. 27
  
VIII.   MOLECULAR  ASSAYS ....................................................................................................................... 29
  
IX.   REGULATORY  OUTCOMES ............................................................................................................. 29
  
X.   GLOSSARY  ........................................................................................................................................... 30
  
  3   Contains Nonbinding Recommendations  
 
XI.   FDA  GUIDANCE  DOCUMENTS  AND  CLSI GUIDELINES  REFERENCED  ............................. 33
  
APPENDIX  I - MIGRATION  STUDIES  FOR  BLOOD  DONOR  SCREENING  ASSAYS  ....................... 35
  
APPENDIX  II - STATISTICAL NOTES ......................................................................................................... 37
  
  4   Contains Nonbinding Recommendations  
Assay Migration Studies for In Vitro 

Diagnostic Devices
   
Guidance for Industry and FDA Staff 

 
This guidance  represents  the Food and Drug Administration's (FDA's) current thinking 
on this topic.  It does not create or confer any rights for or on any person and does not  
operate to bind FDA or the public.  You can use an alternative approach if the approach  
satisfies the requirements of the applicable statutes and regulations.  If you want to discuss 
an alternative approach, contact the FDA staff responsible for implementing this 
guidance.  If you cannot identify the appropriate FDA staff, call the appropriate number 
listed on the title page of this guidance.  
I.   Introduction  
This guidance outlines FDAs  regulatory approach for  approval of  Class III  in vitro 
diagnostic devices, as well as  certain licensed1  or certain cleared2  in vitro diagnostic devices  
in cases,  when a previously approved, licensed, or  cleared  assay  is migrating (i.e., 
transitioning) to another system for which assay  performance  has not been evaluated by 
FDA.2   In this guidance the term new system refers to the system (assay, instrument, and 
software) to which the assay is migrating from a previously approved/licensed/cleared  
system.  The term  old system refers to  the  system (assay, instrument and software) which 
was approved/licensed/cleared from  which the assay is migrating to a  currently 
unapproved/unlicensed/uncleared  system.  
This  guidance is  focused  on the  study designs and performance  criteria that should be  
fulfilled in order for a sponsor to utilize  the  migration study approach  in support of the  
change.   FDA will review information from the sponsor, including results of analytical and 
comparison studies outlined in this guidance,  as well as  device descriptions and risk 
analyses,  to determine whether  the  use of the  approved/licensed/cleared  assay with the  new  
system  may  compromise  safety and effectiveness  of the assay.   The guidance  document  
describes information that we recommend you include in a PMA  (premarket approval  
                                                           
1  This guidance does not  apply  to  immunohematology  tests licensed  by  the Center  for  Biologics Evaluation  
and  Research  (CBER).  
2  This  guidance can  be used  for  510(k)  devices where the Replacement  Reagent  and  Instrument  Family  Policy  
(http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm079185.htm)  
does not  apply  (e.g.,  nucleic acid  amplification  tests)  and  devices for  which  transitioning  to  a new  system  
presents specific concerns,  either  because of  the nature of  the analyte and  indications,  or  because of  the specific 
technology  used.    
  1   Contains Nonbinding Recommendations  
application)  supplement, a  BLA  (Biologics License Application)  supplement, or a 510(k)  
(premarket notification).   For devices regulated by OIR  (Office of In Vitro Diagnostics  and 
Radiological Health, within CDRH), sponsors may  contact  OIR,  and for  those regulated by 
CBER, sponsors may contact CBER  to obtain feedback concerning study plans.   
FDA's guidance documents, including this guidance, do not establish legally enforceable 
responsibilities.  Instead, guidances describe the Agency's current thinking on a topic and 
should be viewed only as recommendations, unless specific regulatory or statutory 
requirements are cited.  The use of the word should  in Agency guidances means that  
something is suggested or recommended, but not required.  
II.   Background  
The FDA believes that  the assay migration study paradigm  discussed  in this guidance 
provides  a least burdensome scientific and regulatory pathway for manufacturers to transfer a 
previously approved  or licensed  assay  with full clinical data from an old system  to a new  
system  (not approved. licensed, or cleared).  The paradigm is suitable in cases when 
sufficient knowledge can be derived from the documentation of design controls, risk 
analyses, and prior performance studies on an old system.   
If you make further modifications or iterations of the old or  new  system  you should compare  
back to the original  old system  that has full clinical data when performing new migration 
studies.  However, if the old system  with full clinical data is no  longer  available please 
contact  the appropriate FDA  CDRH  or  CBER Division for further discussion.  
The migration studies approach is related to  the Replacement Reagent and Instrument Family 
Policy  that FDA  uses  for many Class  I  and Class  II  diagnostic devices.3   Similar to that  
policy,  migration studies  rest on the premise that as platform  changes are made throughout  
the lifetime  of an  approved,  licensed, or cleared  assay,  smaller and more focused analytical  
and clinical data sets, along with prior knowledge of device design and performance,  could 
allow for  a determination that  the safety and effectiveness profile of the modified system  has 
not been compromised.  
The assay migration study paradigm  is practical, risk based, and consistent with FDAs  
Critical Path Initiative,  which is intended to help bring new medical products to market  
successfully and efficiently4.  FDA  believes that  with proper control and review, migration 
studies will  meet regulatory thresholds for premarket review in a manner that will be  least  
burdensome for  both companies and FDA while protecting public health.  
                                                           
3  http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm079185.htm.  
4  http://www.fda.gov/oc/initiatives/criticalpath/whitepaper.html  
  2   Contains Nonbinding Recommendations  
III.   Scope 
 
This guidance  is intended to be applied,  where appropriate,  to  licensed donor screening tests5  
and approved  (Class III)  in vitro diagnostic assays, as well as 510(k)  cleared assays for which  
migration to a new system  presents concerns.  Possible scenarios  for assay migration are  
when the  assay  is being transferred from  a manual system to an automated or semi-automated  
instrument  system  or from  a semi-automated instrument system  to a fully automated 
instrument  system, or from one automated instrument system to another  (and vice  versa for  
all scenarios).   A broad variety of methodologies  may use the  migration studies  paradigm  
depending on what is known about the two Systems involved.   Assay transfer may be from  
one approved,  licensed, or cleared  old system  to a new system  that has the same technical  
characteristics.  However, if scientific evidence suggests migration studies  may not  be 
adequate to  predict actual  clinical  testing performance  on the new system, the assay 
migration paradigm  should  not apply and  FDA will  recommend that  traditional  evaluation 
studies  be performed.  
Assay migration studies are ideally suited for  test systems  for which the assay output  (raw  
signal) is  a numeric  result or  is expressed as a signal  to cutoff (S/CO).  Devices  for which a 
numeric  output  is not  available  might  be more difficult to analyze and may not be suitable 
candidates for use of  this approach.  
Migration studies would not be applicable to the following devices or  to system  changes that  
are generally considered significant, such as:  
   systems intended for over-the-counter use,  
   systems intended for prescription  home use,  or  
   devices that do not meet the Critical Considerations criteria stated  below.  
The FDA  strongly  recommends that  sponsors  discuss proposed migration studies with the 
Agency early in the product  design and testing  process  in order  to determine if  the  proposed 
changes are  consistent with the considerations  that would allow for focused testing.  An early 
contact with the  Agency is especially recommended for  an assay being transferred from a 
manual system to an automated or semi-automated instrument system.  For CBER  licensed 
devices, this contact  may  be through an  IND,  or protocol  review,  providing  preliminary 
protocols, data, and justifications prior to performing the migration studies.   The size, nature,  
                                                           
5  FDA  does not  believe that  this guidance is suitable for  use in  its entirety  when  immunohematology  tests (e.g.,  
blood  grouping,  blood  group  antibody  detection  and/or  identification,  crossmatching)  are being  migrated  
because of  the differences in  assay  methodology  and  results reading  and  interpretation  as compared  to  the other  
assays and  systems described  in  this guidance.   If  you  believe that  your  immunohematology  reagents and  
system  can  be evaluated  using  the criteria outlined  in  this guidance,  contact  the responsible review  division  in  
CBER.   Immunohematology  products are reviewed  in  the Devices Review  Branch,  Division  of  Blood  
Applications,  Office of  Blood  Research  and  Review,  CBER.  
  3   Contains Nonbinding Recommendations  
and scope of migration studies we recommend will depend on a detailed  evaluation of the old 
and new systems, the level of regulation appropriate for the product (e.g., PMA,  BLA, or  
510(k)), the performance characteristics of the assay, and the design and scope of the 
analytical testing and clinical trials used to support approval,  licensure, or clearance  of the 
assay on the old system.    
IV.   Critical Considerations  for  Determining Whether  
The Migration Studies Paradigm May Apply To A  
Particular Device  
A sponsor should take into account the following critical considerations in determining 
whether  the migration studies approach is  appropriate for  a particular  product, and describe 
these considerations in the submission:  
	   The intended use and indications for use for the new system  should be unchanged 
from the old system, except for  inclusion of the new system.  
	   Reagent and assay parameters (e.g.,  cutoff)  should be unchanged, except for  very 
minor differences (such as small changes in incubation times)  in order to optimize the 
assay on the new system.  However, the sponsor should provide evidence that the 
changes  do not compromise the assays performance.   
	   Some assay technologies may not be good candidates for the migration studies 
paradigm (e.g.,  assays with relatively high imprecision near the assay cutoff).  
	   Assay and system  technologies should remain unchanged.  All biochemical  (e.g., 
antibody and antigen interactions or DNA probe  construct)  and physical detection 
(e.g., colorimetric, chemiluminescence, or dye binding)  technologies should be 
unchanged from the old system.   Minor differences in hardware instrumentation may  
be appropriate  and  will be evaluated  on a case-by-case basis.  
	   There should be no expected change to the assay performance when run on the new  
system.  However, actual changes will be evaluated in the context of their impact  on 
the clinical use of the assay.  Due to the limited number of  positive and negative  
samples, the migration studies approach is not appropriate to support  changes in 
clinical performance claims.     
V.   Additional Considerations  
In addition to addressing  each of  the critical considerations noted in Section  IV,  you  should 
also include  the information listed below  to demonstrate  the applicability of migration 
studies to the transfer of the assay  from  the  old system  to the  new system.  The information 
in your submission should include,  but is not limited to,  the following:   
  4   Contains Nonbinding Recommendations  
	   Device description, including functional block diagrams  and  hardware  and software 
components for both the old  and new systems  to allow an evaluation of  the changes to  
the new system  when  compared  to the old system.  
	   A  similarities and differences table for  a side-by-side comparison of  assay parameters 
and hardware/software  functions, requirements and design.  
	   A  risk  analysis of the new system  (software/hardware/assay)  using relevant guidance 
6,7 
documents.  
	   Summaries of software data validating functional operation of alerts and alarms in 
real or simulated circumstances.  
	   System  Operator  Manual(s): If the  new system  was  previously approved  or licensed 
with analytes  other  than the one under consideration,  a new  review of the System  
Operator  Manual  may only be called for  if  changes have been made that impact  
safety and effectiveness, or  if  there are assay-specific  sections or changes.  
	   Proposed modifications to the labeling that appropriately describe respective prior  
data and new migration study information.  The sponsor  should consult with FDA  
when determining  whether a dual or separate package insert will be appropriate.  
Inclusion of the old systems  analytical and performance data should be included 
where appropriate.  
In addition,  the sponsor should include documentation  on software and instrumentation for  
the new system.  When appropriate for the device, this documentation should meet all  
recommendations  for  the appropriate Level of Concern.7   To  further minimize risk, studies  
should be performed on the final  production  model  of the new system  that is intended to be 
marketed.  Likewise, studies should be performed using the final release candidate of the 
software and any differences between the release candidate and the final release should be 
evaluated using a risk based approach  and included in the submission for FDA review.  
If  you are using the migration paradigm to migrate an approved Class III assay to an 
instrument that has not previously been  cleared or approved,  or  to move  an  approved Class 
III  manual  assay to an instrument not  previously  cleared or  approved, you should  submit  
documentation describing the  hardware and software design controls,  including design 
verification and validation, along with other  appropriate Quality Systems  documentation. 
(See  21  CFR  Part 820    Quality System Regulation).  For a general discussion of the Quality 
System information that FDA recommends including in premarket applications please also  
refer to the guidance document available at  
http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/uc 
                                                           
6   ISO  14971:2007,  Medical  devices   Application  of  risk  management  to  medical  devices   
7  Guidance for  Industry  and  FDA  Staff:  Guidance for  the Content  of  Premarket  Submissions for  Software 
Contained  in  Medical  Devices,  
. 
http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm089543.htm
  5   Contains Nonbinding Recommendations  
m070897.htm.  In addition, if the instrument manufacturing site has not been inspected as 
part of the original class III assay approval process, then a site inspection may  be conducted.    
VI.   Assay Migration Studies  
This section outlines specific studies that may be appropriate to support assay migration for  
in vitro diagnostic devices.   Before preparing to use the migration studies approach,  you  
should determine whether the  assay is quantitative,  qualitative  or semi-quantitative, 
according to the definitions  in this guidance.   Specifically, for the purposes of this guidance, 
qualitative assays are those that  use numeric  values  (e.g., signal, S/CO),  to determine  
nominal  categorical  assay results (e.g., positive or negative).  Quantitative assays  determine 
numeric  values  which are referenced to a measuring  interval,  and standards that allow  
determination of analyte concentrations.   Section VI.A  below  describes studies  for  
qualitative assays; Sections  VI.B  and VI.C  address quantitative assays  and semi-quantitative 
assays respectively;  and Section VI.D  addresses point-of-care assays.  Special considerations 
for blood screening assays are covered in Appendix I,  Migration Studies for Blood  Donor  
Screening Assays.    
A.   Migration Studies  for  Qualitative  Assays  
1.   Analytical Studies for  Qualitative  Assays  
The evaluations described below are based on the idea that similar studies were  
conducted previously for the  old system.  If the study design of the analytical studies 
conducted for the  old system  were  different from  the design of the studies described in 
this guidance,  please contact  the FDA  for feedback.   If  you believe  that  some of the  
studies outlined in this document  do not  apply to your particular device, you should 
present your justification for FDA review.   
We recommend that you use  fresh clinical  specimens  for all analytical studies.  If  this is 
impractical,  in some cases  you  may substitute or supplement  fresh  clinical  specimens 
with archived  samples.  If  archived  samples  are not available, spiked or diluted clinical  
samples  may be used.  In some  instances, use of otherwise contrived matrix-specific  
samples  may also be  appropriate;  however these should  mimic  clinical  specimens  as 
much as is feasible.  We recommend that you contact FDA if you wish to discuss 
appropriate sample types for these evaluations.  The matrix of any of these alternative  
specimens  should be the same as that specified by the intended use of the  old system.   
a)  Performance  at Low  Analyte  Levels  
  You  should evaluate the performance  of the  assay on the  new system  compared to the  
old system  at low analyte levels (e.g., with dilution panels and seroconversion 
panels).  
   Where available, assay performance at low  positive  analyte levels using 
  6   Contains Nonbinding Recommendations  
dilution panels should be based on  international standards (e.g.,  World Health 
Organization  (WHO)  standards, Paul  Ehrlich Institute  (PEI)  standards)  and 
compared with  the old system.  
	   If available and appropriate, test well-characterized seroconversion panels 
similar in number and type to the panels originally used to support  
approval/licensure/clearance.  The seroconversion panels should be run on 
both the old system  and the new system.  
b)   Precision  
This section describes precision study designs  including panel composition.  
(i)  Composition  of Precision Panel   
The categorical  result  of a  qualitative test  is determined using the numeric  test  
data and a cutoff(s) (e.g.,  a numeric  threshold),  which define numeric  ranges that  
correspond to the final  result  categories.  For  a  qualitative test with two 
categorical  results, a  cutoff (one threshold) is used to  define  positive and negative 
results of the test.  When the observed numeric  test data  exceeds the threshold, the  
final  result is considered positive (or  reactive, detected).  When the  observed 
numeric  test  result is below the cutoff, it is considered negative (or  not reactive,  
not detected).   
Qualitative assays  discriminating  between  two classes of subjects (non-diseased 
vs diseased)  can fall into two groups:  1)  assays used in situations where  non-
diseased subject  samples  have  a  true zero  concentration of the  analyte of interest, 
and  2)  assays used in situations where  non-diseased subject  samples  have  a  
detectable  analyte  concentration.  For the latter, the cutoff  was chosen to optimize  
clinical sensitivity and clinical specificity of the assay based on a  clinical  data set.   
Appropriate precision panels for  these two types of assays,  as well as assays that  
produce equivocal results, and/or have a re-test zone, are  discussed in more detail  
in (a)-(c), below:  
(a)  When  non-diseased subject samples  have a detectable amount of  
analyte.  
For the  non-diseased subject samples  that  have  a  detectable  amount of  analyte  
the cutoff of the assay is higher than the limit of the blank.  A  useful  
characteristic  of the cutoff is that a sample with  a  concentration  (determined 
by the mean signal to cutoff  value from a large a series of replicate  
measurements)  at the cutoff  yields a  positive  result 50% of the time and a  
negative  result 50%  of the time when a large  number of replicates of that  
sample  are run under stipulated conditions  (see Figure 1 below).   We denote  
this concentration as C .  
50
  7   Contains Nonbinding Recommendations  
Figure 1.  Results of a qualitative assay  (probability density function)  for 
a sample with a concentration at the cutoff  measured multiple times.         
For samples  with concentrations exceeding C , one expects to see positive 
50
results more than 50% of the time,  and similarly for samples  with a 
concentration below C , one expects to see positive results less than 50% of  
50
the time.  In this guidance we refer to an analyte concentration that yields, 
upon evaluating  many replicates, a positive result 95% of the time (and a 
negative result 5% of the time)  as a Low  Positive concentration (C  
95 
concentration).  We refer to a sample  concentration which yields a positive 
result 5% of the time (and negative result 95% of the time)  as a High  Negative 
concentration (C  concentration).  Samples  with concentrations  of analyte 
5 
close to  C  and C  as determined  by the old system  are  recommended for the 
95  5 
within-laboratory precision (see CLSI8  document  EP12).  The  panel should 
consist of at least  four  members, as described below  (also, see Figure 2):   
	   A  True Negative sample: a sample with a  true  analyte concentration of  
zero.  
	   A  High Negative sample:  a sample  that  repeatedly  tests negative 
approximately 95% of the time  and positive 5% of the time by the old 
system.  One should expect that the same concentration tested by the 
new system  will  also produce negative results approximately 95% of  
                                                           
8  Clinical  Laboratory  and  Standards Institute.   CLSI  documents referenced  in  this guidance are listed  in  Section  
XI  of  this document.  
  8   Contains Nonbinding Recommendations  
the time  (C  concentration as determined by the old system).    
5 
	   A  Low  Positive sample:  a sample  with an analyte  concentration 
around C  as determined by the old system.  Repeatedly testing  this 
95 
sample  by the old  system  should give a positive result  approximately 
95% of the time  and a negative result 5% of the time.   One should 
expect  that  the same concentration tested by the new system  will  also 
produce positive results approximately 95% of the time.   Note that if  
the LoB is used as a cutoff,  then the concentration C  is the same as 
95 
the LoD.  
	   A  Moderate Positive sample:  a sample  with a concentration close to 
the cutoff,  and at which one observes  positive results by the old system  
approximately 100% of the time (e.g., a sample with a signal  
approximately two to three times the signal at  the cutoff if the  
cutoff=1.0,  or a sample with concentration approximately two to three 
times  the 95% LoD  if the cutoff  is based on LoB).   
Figure 2.  Relationship between percent of positive results and the analyte 
cutoff concentration.  
For  the details  of  how the C  and C  concentrations can be evaluated from the 
95  5 
previous precision studies of the old system,  see Appendix  II:  Statistical  
Notes, 1.  For the  precision study of the new system, it is not necessary to 
have the High Negative and Low  Positive samples at exactly C  or C of the 
5  95  
old system.  If the High Negative and Low  Positive samples in the precision 
study of the new system  are close enough to the cutoff that the standard 
  9   Contains Nonbinding Recommendations  
deviation (or percent  coefficient of variation  (CV) is approximately  constant  
over the range around the cutoff, the C  and C  of the new system  can be 
5  95 
evaluated from this precision study (see Appendix II:  Statistical Notes, 1).   
(b)   When non-diseased subject samples  have a true zero analyte 
concentration.  
When  non-diseased  subject  samples  have  a true zero analyte concentration  
there are two types of assays:  (1)  assays for which samples  with zero 
concentration have  a  distribution of  numeric  signals  and the cutoff of the 
assay is the limit of blank (with some type I error, for example, 5%);  and (2)  
ultrasensitive  assays for which samples with zero analyte concentration 
almost always have a negative assay  result  (type I error is close to zero).   
These two types of  assays are discussed further in the two bullets below.  
	   Consider  assays  where  samples with zero analyte concentration have  a  
distribution of  numeric  signals  and the limit of blank is used as a 
cutoff.   In this case  the concentration C  is the same as the limit of  
95 
detection (LoD) and zero concentration (no analyte present in sample)  
is C  as illustrated in Figure 3, below.  The precision panel should 
5 
consist of at least  the  following three members:  True  Negative, Low  
Positive (around LoD) and Moderately Positive.   
Figure 3. Relationship between the percent of positive results and the 
analyte concentration  where True Negative samples produce numeric  
results and the C  concentration is the LoD of the assay.  
95 
  10   Contains Nonbinding Recommendations  
	   For ultrasensitive assays  that employ, for example,  a signal  
amplification methodology (e.g.,  real-time PCR),  the following 
approaches for  precision  panel members  are recommended.  For  
ultrasensitive assays,  the concentration range that  spans High Negative 
(around C ) to Low Positive (around C =LoD) is narrow with respect  
5 95
to the observed concentration range of clinical specimens.  Due to this 
narrow range, it may be difficult to prepare  a sample  with C
5  
concentration.      
  If less than 10% of all subjects positive by the old system  have an 
observed concentration less than C  then samples at the C  
95,  5 
concentration could be excluded  from  the precision  panel.  In this 
case, samples  which compose the  precision  panel  should  include the 
following concentrations:  True Negative, Low Positive (around C )  
95
and Moderately Positive.   
If more than 10% of all subjects positive by the old system  have an 
observed concentration less than C , then samples  which compose the 
95
precision  panel  should  include the following concentrations:  True 
Negative, Low Positive (around C ), samples  in the range of C  to 
95 20 
C and Moderately  Positive  as illustrated in Figure  4, below.  
80  
Figure 4.   Relationship  between the percent of positive results and the 
analyte concentration  for an ultrasensitive assay showing a narrow  
concentration range between C  and C .  
5  95
  11   Contains Nonbinding Recommendations  
(c)  When an assay with  a numeric  value produces an equivocal result and/or 
has a re-test zone.  
If your  assay  with numeric  values produces an equivocal result  and/or has a 
re-test zone,  then the assay  has  two cutoffs, E  and E     
1  2: 
If  S/CO < E1 then the assay  result is Negative  
If E   S/CO  E  then the assay  result is equivocal  or  in the re-test  zone  
1  2 
If S/CO > E  then the assay  result is Positive  
2 
As an example, the  numeric  values of the assay with equivocal results defined 
as having S/CO  from  E  to E  are  shown graphically in Figure 5, below.   
1  2 
Figure 5.   Relationship of  numeric  values and result  categories for an  
assay with equivocal results.  
The C  and C  concentrations for the old system  are calculated for  cutoffs  E  
5  95  1 
and E  respectively using the same method as described in Appendix II:  
2 
Statistical Notes, 1.  In this case, samples  which compose the  precision panel  
should include  the following concentrations:  True Negative;  near  the 
equivocal (and/or re-test) zone:  near  the C  for cutoff E  and near the  C  for  
5  1  95 
cutoff E ; and Moderately Positive.   
2
In  addition  to the samples described  for all panels  (a-c)  above, you should run the 
appropriate control material  (negative and positive controls)  and calibrators in the 
precision study.   
(ii)    Within-Laboratory  Precision  Study   
We recommend that you conduct in-house within-laboratory precision studies (to 
supplement the external site reproducibility studies described below in Section 
VI.A.1.b.iii).  When  appropriate  and justified, the in-house within-laboratory 
precision study may not be necessary, such as  (1) if you  established that the new  
system  only needs to be recalibrated at relatively long time  intervals (e.g., 6 
months or more)  and any other concerns can be appropriately addressed by the 
reproducibility study, or (2)  if the new system  is recalibrated daily, so that  
  12   Contains Nonbinding Recommendations  
calibration cycle variability is  inseparable from day-to-day variability (which is 
assessed by the reproducibility studies described below)  and  any other concerns 
can be appropriately addressed by the reproducibility study.  
It may be sufficient to perform within-laboratory precision studies  only on  the 
new system.  However, if the study design or composition of the precision panel  
of the old system  precision study was very different from that described in this 
guidance, it may be important to perform  the precision study  on the old system  as 
well.   The within-laboratory precision study described below  is based on CLSI  
document EP05.  
Sources of variability  we recommend  for the within-laboratory precision study are 
at least 12 days of testing, with 2 runs per day, and 2 replicates of each sample per  
run.  These 12 days are not necessarily consecutive.  If  the system calibration 
variation composes a significant portion of the total system variation,  or the 
calibration interval fits within the time  frame of the studies,  then at least 2 
calibration cycles should be included in the study design;  otherwise you should,  
provide your  rationale for not including an evaluation of the variation introduced 
due to instrument calibration.  For each cycle, days at the beginning and end of  
the cycle should be included (e.g., 3 days at the beginning and 3 days at the end 
for each cycle).  You should include other additional sources of variability in the 
design of the study, if they are important to  the specific assay (e.g., operators, 
lots, etc.).  In such cases, overall modification to the variables might be possible 
(e.g., spreading days of testing between different operators).  If analytical and 
clinical performance is similar across all matrices that are included in the intended 
use of the old system, then establishing performance of the new system  using the 
most commonly employed matrix may suffice.   
(iii)   Reproducibility  Study   
We recommend you perform the  reproducibility  study based on a modification of  
CLSI  document  EP05  on the new system.  The panel composition and analyte  
levels for this study should be the same as described above (in Section 
VI.A.1.b.i).   Sources of  variability should  include  testing for  at  least  5 days, 2 
runs per day, with 3 replicates of each panel member  per run,  at 3 laboratories  of  
which  at least  2  are  external sites.   Other sources of variability might be 
applicable if relevant to the specific assay (e.g.  operators).  If analytical and 
clinical performance is similar across all matrices intended for use with  the old 
system, then establishing performance of the new system  using the most  
commonly employed matrix may suffice.    
For each concentration level, similar information should be available for the old 
system.  Otherwise, you should perform  a new reproducibility study for the old 
system  with study design and concentration levels as described in this section.  
  13   Contains Nonbinding Recommendations  
2. 	  Comparison  Studies for  Qualitative  Assays  
You should perform  comparison studies  using  comparison panels  described below.   
However, minor changes to the old system  might not warrant  performing all comparison 
studies.  The extent of the  utility of these studies can  be evaluated on a case-by-case basis 
in consultation with the FDA.   
a)  Comparison  Panels  
For each analyte, the qualitative assay comparison panels  should consist  of  the 
following:  
	   Panels of samples  known  to be positive or  negative for a  specific assay  on the 
old system  (in order to evaluate the same assay on the new system).  We 
suggest that the positive and negative panels have at least  100 panel members  
each.    
Positive panel members  should be prepared so that approximately 60%
80% of the samples have  analyte levels close to the cutoff.  Of these 
samples, approximately one half should be close to the C  (or LoD)  of the 
95 
old system  and the other half should be Moderate Positive samples.  The 
remaining positive samples should evenly cover the full detection range of  
the assay.   
Negative panel members  should be prepared so that approximately 30%
40% are High Negatives (close to C  of the old system).  Because FDA is 
5 
assessing clinical effectiveness based upon the result agreement for the 
assay performed on the two instruments, these samples can have an 
analyte concentration below the cutoff such that repeat testing of these 
samples should be negative approximately 95% of the time.  Alternatively, 
these High Negative samples may be obtained from  archived  clinical  
samples giving a signal  just below the cutoff.   For  ultrasensitive  assays, 
negative panel members should include at least 100 True  Negative 
samples.  
 	  If  the  assay  produces an equivocal result  and/or has a re-test zone, then the 
assay  has two cutoffs, E  and E . For the purpose of  defining acceptable 
1  2
concentration ranges of negative and positive panel members, consider the 
lower bound of the equivocal or re-test zone as E  and the upper bound as E  
1  2 
noted below:  
If S/CO < E  then the assay  result is Negative  
1 
If E   S/CO  E  then the assay  result is equivocal,  or  in the  re-test  zone.  
1  2 
If S/CO > E  then the assay  result is Positive  
2 
  14   Contains Nonbinding Recommendations  
Positive panel members  should be prepared so that approximately 60%
80% of the samples have analyte levels close to the cutoffs.  Of these 
samples, approximately one half should be close to the C  calculated 
95, 
using E  based on the precision of the old system,  and the other half  
2 
should be Moderate Positive samples.  The remaining positive samples 
should evenly cover the full detection range of the assay.  Among the 
samples close to the C , some samples should be in the equivocal  zone 
95
(and/or in the re-test  zone),  as defined by the old system.  
Negative panel members  should be prepared so that approximately 30%
40% are High Negatives (close to the C  calculated using E  based on the 
5  1 
precision of the old system).  Because FDA is assessing clinical  
effectiveness based upon the result agreement for the assay performed 
with  the two systems, these samples can have an analyte concentration 
below the cutoff such that  repeat testing of these samples should be 
negative approximately 95% of the time.  Alternatively, these High 
Negative samples may be obtained from  archived  clinical samples giving 
a signal just below the lower bound of the equivocal or re-test zone (E ).   
1
Among the samples close to the C , some samples should be in the 
5
equivocal (and/or  re-test) zone as defined by the old system.  
	   It is preferable to use non-contrived  clinical  samples  to create the panel  
members.  However, where positive  samples are not  available  or volumes are 
low, you  should work with the FDA to define acceptable sample  types.  
Positive  panel members may be diluted in a clinical  matrix  in some cases.   
Preferably, individual negative samples should be used for each dilution.  
Spiked samples  may be  acceptable, but only from individual strong positives 
in the appropriate  clinical  matrix  (i.e., the same sample  cannot be used to 
prepare multiple panel samples).  
	   Archived samples  are acceptable if stored in accordance with the package 
insert instructions.  The samples  should be randomized and masked.  
b)   Comparison  Study  Design  
You should test the comparison panels on the old system  at a minimum of one site.  
This may be done  in-house.  However, we recommend use of  at least two of the old 
systems  to better assess  systematic differences  between different  old systems.  The 
new system  should be tested  at a minimum of  three  sites (one  may be in-house)  with  
one  or more reagent kit lots.   Each panel member  should be  tested at least  four  times:  
once with the old system  and three  times with  the new system.  You should send the  
same positive and negative panels  to each site, rather than dividing  the panel  between  
the three sites.   Three different  builds  with unique serial numbers  of the new system  
should  be tested,  one unique serial numbered system  at each of the three sites.  
3. 	  Statistical Analysis of  Data  
  15   Contains Nonbinding Recommendations  
We recommend you  include the  information described in Sections  a-c  below  for each  of  
the respective studies, in your submission:  
a)  Within-Laboratory  Precision  Study   
	   For each sample  tested, we recommend you  present  the mean value with 
variance components (standard deviation and percent CV)  for  numeric  values 
for  the new system.  In addition, you should include the percent of values 
above and below the cutoff  for each sample.  You should  also  provide an 
estimation of C  and C  of the new system  (see Appendix II:  Statistical  
5  95 
Notes, 1).  
	   For each analyte concentration, you should provide similar information for the 
old system.  You can obtain this information  from the precision study  you 
originally used to demonstrate the performance of the  old system,  if  the study 
design and the analyte concentration levels are comparable to those used to 
assess the new system.   You can utilize  information about  variance 
components  (standard deviation and percent CV)  from the precision study 
found in the old system  labeling.  However, if the study design and analyte 
concentrations for the old system  are different  from  those described in this 
document,  a new precision study for the old system  should be performed  to 
allow for comparison between systems.  
	   For  similar  analyte concentrations, we recommend you  provide repeatability 
(within-run precision)  and within-laboratory precision (standard deviation and 
percent CV)  of the New  and old systems  (precision profiles of the New and 
old systems).  In  addition, you should provide the ratio of the standard 
deviations of the New and old systems along with the 95% confidence interval  
for this ratio.  The confidence interval can be based on the F-statistic for a 
ratio of variances  (see Appendix II:  Statistical Notes, 2).  
b)  Reproducibility  Study  
	   For each analyte concentration level, we recommend you  present  the mean 
value with variance components (standard deviation and percent CV)  for the 
new system,  for  each site separately and for  all  sites combined.  In addition, 
for each panel member,  you should include  the percent of values above and 
below the cutoff,  for each site separately and for all sites combined.  You 
should also provide an estimation of C  and  C  of the new system,  for each 
5  95 
site separately and for all sites combined.   
	   For each analyte concentration level, we recommend you  present  similar  
information for the old system.  This information can be taken from the 
precision study originally used to demonstrate the performance of the old 
system  if  the study design and the analyte concentration levels are comparable 
to those used to assess the new system. The information about variance 
components (standard deviation and percent CV) can be obtained from  the 
  16   Contains Nonbinding Recommendations  
precision study found in the old system  labeling.  If the study design and 
analyte concentrations are different than those described in this document, a 
new precision study for the old system  should be performed.  
	   For  similar  concentrations, you should provide repeatability  (within-run 
precision),  within-laboratory precision (standard deviation  and percent  CV)  
and reproducibility separately and combined  over three sites  for  the new  
systems  and old system  (precision profiles of the new system  and old system).  
In  addition, we recommend you  provide the ratio of repeatability standard 
deviations along with 95% confidence intervals and the ratio of the 
reproducibility standard deviations  of  the New  and old systems.   The 
confidence intervals  for the ratios can be based on the F-statistic for a ratio of  
variances  (see Appendix II:  Statistical Notes, 2).  
c)   Comparison  Panels  
	   You should provide a  scatter-plot of S/CO  or any other  numeric  values that  
differentiate between positive (reactive) and negative (non-reactive)  of the old 
system  (X-axis)  vs. S/CO of the new system  (Y-axis)  with descriptive 
statistics, for data generated at each site as well as  for  all sites combined.   
Both axes should have the same scale, and the line of identity (y=x) should be 
presented.  The same scale on the axes should be applied to the data from each 
site.   In addition you should provide similar scatter plots for negative and 
positive specimens separately.  
	   You should provide an estimation of systematic differences between the 
numeric  values generated by the old system  and the new system  at each site 
and for  all sites combined  (CLSI  document  EP09).  You should perform the 
appropriate regression analysis (Deming regression, see Appendix II:  
Statistical Notes, 3),  which accounts for the random errors associated with the 
old  and new system  measurements  and provide the 95% confidence intervals 
of the slope and intercept from the regression analysis.   The  emphasis  should 
be placed on estimating  the systematic difference between the numeric  values 
of the old and new systems around the cutoff.   You should also calculate the 
average systematic difference separately for the Negative, High Negative, 
Low  Positive and High Positive samples of the comparison panel.  
	   We recommend that you present tables  (e.g.,  with old system  results defined 
by the columns and new system  results defined by the rows),  for data derived 
from  each site and for all data combined  (see  Appendix  II: Statistical Notes,  
4).   For the qualitative assays with equivocal (and/or re-test  zone), the results 
of  the comparison study should be presented in 3-by-3 tables from data 
derived from each site and for all data combined (see Appendix II: Statistical  
Notes, 5).  Based on these tables, you should calculate  positive and negative 
percent agreements at each site along  with the corresponding 95% two-sided 
confidence intervals (for confidence intervals, see Appendix  II:  Statistical  
Notes, 6).  In addition, you should provide the positive and negative percent  
  17   Contains Nonbinding Recommendations  
agreements averaged over three sites with the corresponding 95% two-sided 
confidence intervals.   Because the same samples  are used at all three sites, we 
suggest  that  a bootstrap approach may be useful  for calculating such 
confidence intervals.   
	   For qualitative assays with equivocal results  (and/or a re-test zone), the 
comparison study data should be analyzed as having three ordinal categories 
(e.g., negative, equivocal, positive).  Note that the purpose of a migration 
comparison study is to evaluate the extent of differences between the numeric  
values obtained from the old system  and numeric  values obtained from the 
new system.  While re-testing may be indicated in the package insert, this 
additional testing is  unnecessary to fulfill the migration comparison study 
objective.   The initial  numeric  values should be used in the numeric  analysis.   
For qualitative assays  with equivocal results (and/or re-test zone), we 
recommend that you present tables of agreement including positive, negative 
and equivocal  (and/or re-test)  as categorical results for data derived for each 
site and for all sites combined (see Appendix II: Statistical Notes, 5).  Based 
on the three-by-three tables of agreement, you should calculate positive and 
negative agreements along with 95% two-sided confidence intervals,  and 
percents of different results by the new system  for the equivocal results by the 
old system  for each site separately and for all sites combined.  From the three
by-three table, you should calculate the  percent of equivocal  (and/or re-test)  
results reported by the new system  that  are discordant with the equivocal  
results by the old system.  For evaluation of the  percents of different results 
by the new system  for the equivocal results by the old system  that  reflect the 
natural variability between two measurements by the old system, you should 
present an allowable total difference zone and perform calculations described 
in Section VI.B.3.c,  below (and in Appendix II:  Statistical Notes, 7 and 10).   
4. 	  Acceptance  Criteria  for  Qualitative  Assay  Migration  Studies   
In  addition to the acceptance criteria for performance of the new system  at low levels of  
analyte and for seroconversion panels (if applicable),  we recommend you apply the 
following criteria to demonstrate that there are no changes to performance characteristics 
that could affect the safety and effectiveness  of the device:   
	   The systematic difference between numeric  values (e.g., signal  output, S/CO)  of  
the new  and old systems  should be either  not  clinically significant  and not  
statistically significant,  or, if statistically significant,  should not be clinically 
significant  (see Appendix II: Statistical Notes,  8).   
	   The ratio of standard deviations in the precision studies (reproducibility and 
within-laboratory precision)  of the old and new systems should be either  not  
  18   Contains Nonbinding Recommendations  
clinically significant  and not  statistically significant or,  if statistically significant,  
should not be clinically significant (see  Appendix II:  Statistical Notes, 2 and 8).  
	   Conceptually, the new system  measurements can be considered comparable  to the 
old system  measurements if the new system  measurements of a sample are similar  
to the repeated evaluations  of  the same sample  when run on  the old system.  For  
the old system  measurements,  one can expect high agreement between repeated 
measurements for the samples  with high concentrations of analyte giving 
measurement  results  far from the cutoff,  and some degree of discordance for the 
samples  with concentrations measuring close to the cutoff.  
In the study using  comparison panels, the lower limits of  the 95% two-sided 
confidence intervals for the positive and negative percent agreements between  the  
new system  and the old system  should be higher than 90%  (see Appendix  II:  
Statistical Notes,  9).  Discordant  results between the Old  and new systems  can  
only  occur with samples  close to the cutoff  and not with moderate  or  high  positive  
samples by the old system  (similarly, not with  moderate or  low  negative samples  
by the old system).  
	   You  should investigate any  statistically or clinically significant  differences found 
between the two systems (e.g.,  in precision  testing performance  or  any systematic 
difference), and perform risk assessments  to determine the  percentage of the 
intended use population that  would be affected by such a  difference.  
B.  Migration  Studies for  Quantitative  Assays  
1. 	  Analytical Studies  for  Quantitative  Assays  
If  you believe  that  some of the  studies described in this section do not  apply to your  
particular device, you should describe your reasoning in detail in your application  to 
FDA.  If the design of the analytical studies conducted for the old system  were different  
from those described in this guidance, please contact  FDA.  
We recommend that you use fresh clinical specimens for all analytical studies.  If this is 
impractical in some cases you may substitute or supplement fresh clinical  specimens with 
archived  samples.  If  archived  samples  are not available, spiked or diluted clinical  
samples  may be used.  In some instances, use of otherwise contrived matrix-specific 
samples  may also be appropriate;  however these should mimic clinical specimens as 
much as is feasible.  We recommend that you contact FDA if you wish to discuss 
appropriate sample types for these evaluations. The matrix of any of these alternative 
specimens should be the same as that specified by the intended use of the old system.    
a)  Performance  at Low  Analyte  Levels   
For assays that were previously approved  or licensed  with a specified LoB  (limit of  
blank)  and LoD  (limit of detection),  the same evaluations  should be repeated with the 
  19   Contains Nonbinding Recommendations  
new system.  The study  should demonstrate that  the LoB and LoD are very similar for  
both systems  (a protocol is described in CLSI  document  EP17).   Specifically,  the 
sample  with  a  concentration at the  LoD  (reported as analyte detected approximately 
95% of  the time,  measured by the  old system)  should  also be  reported as analyte  
detected approximately 95% of the time,  if measured by the  new system.  See Figure  
6  below  regarding the LoD.  
Figure  6.  Relationship  between  the signal distributions from multiple 
measurements of  a blank  sample and a sample with an analyte concentration at  
the Limit of  Detection.  
The limit of  quantitation  (LoQ,  or lower limit of measuring range)  of the  new system  
should be estimated and compared with the  LoQ of the  old system  (see CLSI  
document  EP17)  and should be similar to that of the  old system.  The specification 
criteria for the LoQ  of the  new system  should be the same as for the  old system.   We  
also recommend that  the  LoQ correspond to an analyte concentration level used in the  
precision studies.  
b)  Precision  
This section describes precision study designs including panel composition.  
(i)  Composition  of Precision  Panel  
We recommend you evaluate samples with the following levels of analyte:  
   Lowest limit of the measuring range  
  20   Contains Nonbinding Recommendations  
   A level of analyte below the medical decision point  
   Around the medical decision point  
   A level of analyte above the medical decision point  
   Upper limit of the measuring range.  
In addition, you should run the appropriate control material  and calibrators 
associated  with the test kit  in the precision study.  
If the assay has more than one medical decision point, then samples with 
concentrations around these medical decision points should be evaluated.  It is 
understood that some assays will not have a specific medical  decision point, but  
rather a range of values; in such cases, the panel should contain samples scattered 
throughout the measuring range of the assay.  
(ii)   Within-Laboratory  Precision  Study  
We recommend that you conduct in-house within-laboratory precision studies (to 
supplement the external site reproducibility studies described below in Section 
VI.B.1.b.iii).   When appropriate  and justified, the in-house within-laboratory 
precision study may not  be called for, for example, (1)  if  the manufacturer  
established that the new system  only needs to be recalibrated at relatively long 
time intervals (e.g., 6 months or more)  and any other concerns can be 
appropriately addressed by the reproducibility study, or (2)  if the new system  is 
recalibrated daily, so that  calibration cycle variability is  inseparable from day-to
day variability (which is assessed by the reproducibility studies described below)  
and any other concerns can be appropriately addressed by the reproducibility 
study.   
It may be sufficient to perform  within-laboratory precision studies  only  on  the 
new system.  However, if the study design or composition of the precision panel  
of the old system  precision study was very different from that described in this 
guidance, it may be important to perform  the precision study  on the old system  as 
well.   The within-laboratory precision study described below  is based on CLSI  
document EP05.  
Sources of variability for the within-laboratory  precision study which we  
recommend you  include are at least 12 days of testing, with 2 runs per day, and 2 
replicates of each sample per run.  These 12 days are not necessarily consecutive.  
If system calibration variation composes a significant portion of the total system  
variation,  or the calibration interval fits  within the time  frame of  the studies,  then 
at least 2 calibration cycles  should be included in the study design;  otherwise you 
should provide your  rationale for not including an evaluation  of the variation 
introduced  due to instrument calibration.   For each cycle, you should include days 
at the beginning and end of the cycle (e.g.,  3 days at the beginning and 3 days at  
  21   Contains Nonbinding Recommendations  
the end of each cycle, for each cycle).  You should include other  additional  
sources of variability in the design of the study if they are important to the 
specific assay (e.g.,  operators, lots, etc.).  In such cases  overall modification to the 
variables might be possible (e.g., spreading days of testing between different  
operators).  If analytical and clinical performance is similar across all matrices 
that are included  in the Intended Use of the old system, then establishing 
performance of the new system  using the most commonly employed matrix may 
suffice.   
(iii)   Reproducibility Study  
We recommend you perform the reproducibility  study based on CLSI  documents 
EP05  and EP15 on the new system.  The panel composition and analyte levels for  
this study should be the same as described for  the within-laboratory precision 
study above (Section VI.B.1.b.ii).  We recommend  that  sources of variability 
should include testing for  at least  5 days,  2 runs per day, with 3 replicates of each 
panel member per run at 3 laboratories (1 in-house and 2 external sites).  Other  
sources of variability might be applicable if relevant to the specific assay (e.g., 
operators, etc.).  If  analytical and clinical performance is similar across all  
matrices that are indicated for  the old system, then establishing performance of  
the new system  using the most commonly employed matrix may suffice.   
For each concentration level, similar information should be available for the old 
system.  If this is not the case, a new reproducibility study for the old system  
should be performed with study design and concentration levels as described in 
this section.  
c)   Linearity  Study  
We recommend that you evaluate linearity for the  new system  according to CLSI  
document  EP06.  The degree of linearity can be quantified using the maximum  
deviation from linearity (i.e.,  the delta described in CLSI document EP06).  Your  
linearity study results should demonstrate that the delta of the new  system  is not  
greater  than the observed delta in the linearity studies of  the old system.   You should 
determine  the appropriate number of replicates in the linearity study for  the new  
system  based on  the precision studies of the new system.  
2.   Comparison  Studies  
You should perform  comparison studies using comparison panels.  Relatively minor  
changes to the old system  might not warrant all comparison studies.   The extent of the  
utility of these studies can  be evaluated on a case-by-case basis in consultation  with the 
FDA.   
  22   Contains Nonbinding Recommendations  
a)  Comparison  Panels   
For each analyte, the composition of the quantitative assay comparison panels  should 
consist  of  at least 180 samples9,  including the following:  
	   150 of the 180 samples  should span the measuring range of the assay with 
approximately equal numbers of samples at low, medium and high analyte 
concentrations.  
	   If the performance of the assay at low level concentrations is clinically 
important, the remaining panel  members should consist of  at least 30 samples  
(or  about 15%-20% of  the total)  that  should be patient samples  with 
concentration at or near zero.  The zero-level  samples may need to consist of  
different matrices and/or  be from persons with unrelated medical conditions.  
	   It is preferable to use non-contrived clinical  samples.  However, where 
clinical  samples are not  available,  or volumes are low, pooling is a possible 
strategy.  If pooling would not be efficacious, then  dilutions, made serially of  
individual  samples  with a high analyte concentration  diluted into  appropriate  
clinical  matrices,  can be used.  Spiked samples are acceptable, if they are 
prepared  from individual  samples  with high analyte concentrations  in  clinical  
matrices  (i.e., the same sample  should not  be used repetitively).  
 	  Archived samples  are acceptable if stored in accordance with the package 
insert instructions.  Samples  should be masked,  and randomized with respect  
to the  order  in which they are run.  
 	  The  panel should consist of appropriate analyte-specific members.   For  
example, different subtypes or strains of  an  infectious agent  should be 
included when  applicable.  
b)  Comparison  Study  Design  
You should test the comparison panels on the old system  at a minimum of one site.  
This may be done in-house.  However, you may want to use more than one old 
system  to better assess instrument bias.  The new system  should be tested at a 
minimum of three sites (one may be in-house) with at least one reagent kit lot.   Each 
panel member should be tested at least four times: once with the old system  and three 
times with the new system.  You should send the  same positive and negative panels to 
each site, rather than dividing the panel between the three sites.   Three different  
builds of the new system  should be tested, one at each of the three sites.  
3. 	  Statistical Analysis of  Data   
                                                           
9  For  more information  on  sample size,  see  Appendix  II:  Statistical  Notes,  7.   
  23   Contains Nonbinding Recommendations  
a)  Within-Laboratory  Precision  Study   
    For each sample  tested, we recommend you present  the mean value with 
variance components (standard deviation and percent  CV)  for the new system.   
	   For each analyte concentration, you should present  similar information for the 
old system.  This information can be taken from the precision study originally 
used to demonstrate the performance of the old system  if the study design and 
the analyte concentration levels are comparable to those used to assess the 
new system.  The information about variance components (standard deviation 
and percent CV) can be obtained from the precision study found in the old 
system  labeling.  If the study design and analyte concentrations are different  
than those described in this  guidance  document, you should perform  a new  
precision study for the old system.  
	   For each analyte concentration,  (using precision profiles of the New and old 
systems)  we recommend you provide 95% confidence intervals for  
repeatability  and within-laboratory precision (standard deviation  and percent  
CV) of the New and old systems    In addition, we recommend you provide the 
ratio of the repeatability standard deviations of the New and old systems and 
the ratio of within-laboratory standard  deviations along with the 95%  
confidence interval for these  ratios.  The confidence interval can be based on 
the F-statistic for a ratio of variances.  
b)  Reproducibility  Study  
	   For each sample tested, you should present  the mean value with variance 
components (standard deviation and percent CV)  for the new system  for each 
site separately and for all sites combined.   
	   For each analyte concentration level, you should present  similar information 
for the old system.  This information can be taken from the precision study 
originally used to demonstrate the performance of the old system  if the study 
design and the analyte concentration levels are comparable to those used to 
assess the new system.  The information about variance components (standard 
deviation and percent CV) can be obtained from the precision study found in 
the old system  labeling.  If the study design and analyte concentrations are 
different than those described in this document, a new precision study for the 
old system  should be performed.  
	   For  similar  concentration levels,  you should provide repeatability  (within-run 
precision),  within-laboratory precision (standard deviation and percent  CV)  
and reproducibility separately and combined  over three sites  for  the new  
systems and old system  (based on precision profiles of the new system and  old 
system).   In addition, you should provide the ratio of repeatability standard 
deviations along with 95% confidence intervals and the ratio of the 
reproducibility standard deviations  of the New and old systems.  The 
  24   Contains Nonbinding Recommendations  
confidence intervals for the ratios can be based on the F-statistic for a ratio of  
variances  (see Appendix  II: Statistical Notes, 2).  
c)   Comparison  Panels   
	   You should  provide a  scatter-plot of  numeric  values of the old system  (X
axis)  vs. numeric  values of the new system  (Y-axis)  with descriptive statistics 
for data at each site,  as well as for all sites combined.   Both axes should have 
the same scale and the line of identity (y=x), and  the same scale on the axes 
should be applied to the data from each site.  
	   You should provide an estimation of systematic differences  between absolute 
numeric  values by the New and old systems  (CLSI  document  EP09)  for  each 
site and for  all sites combined.  You should perform an appropriate regression 
analysis (such as a Deming regression) which accounts for the random errors 
associated with the Old  and new system  measurements, and  provide the 95%  
confidence intervals of the slope and intercept from this  analysis.  We 
recommend that, for the data from each site and for the combined site data, 
you draw the regression line on the corresponding scatter plots and plot the 
fitted lines (for each site and all sites combined) on the same corresponding 
figures.  Using the regression equation, you should calculate the systematic 
bias at  all  medically important points  along with  95% confidence intervals.    
	   Conceptually, the new system  measurements can be considered comparable to 
the old system  measurements if the new system  measurements of a sample are 
similar  to the repeated evaluations of the same sample when run on the old 
system.  Using the  reproducibility results of the old system,  one  can construct  
limits or boundaries that  define where 95% of the differences between two 
repeated measurements  by the old system  are inside of these limits  (see 
Appendix  II: Statistical Notes,  10).  These limits define an  Allowable Total  
Difference (ATD)  zone (see CLSI  document  EP21) for  differences between 
new system  and old system  measurements.  It is anticipated that no less than 
95% of the sample results will fall within the ATD zones (see Figure 7, 
below).   For details see Appendix  II,  Statistical Notes, 11.  
  25   Contains Nonbinding Recommendations  
ATD  (  95%  of  
samples  in  study)  
                    
Figure 7.   Allowable Total Difference Zone.  
	   You should calculate (i)  the percentage of the samples  at low, medium,  and 
high concentration ranges  that fall within the ATD zone  at each site  and 
averaged over three sites, (ii) the percentage of samples over the entire range 
that fall within the ATD zone with a lower limit of 95%  one-sided confidence 
interval at each site, and (iii) the percentage of samples  over the  entire range 
that  fall within the ATD zone  averaged over three sites  using a bootstrap 
technique, you should  provide  the  95%  one-sided confidence interval  for the 
percentage of the samples over  the entire range that fall within the ATD zone  
averaged over  three sites.  
4. 	  Acceptance  Criteria  for  Quantitative  Assay  Migration  Studies  
In addition to the acceptance criteria for LoB, LoD, LoQ  (see section VI.B.1.a)  and 
linearity  (see section VI.B.1.c),  we recommend that you apply the following  criteria:  
	   The systematic difference between numeric  values  of the new and old systems 
should be either  not  clinically significant  and not  statistically significant, or if  
statistically significant, it  should not be clinically significant. (See Appendix II:  
Statistical Notes, 8).   
	   The ratio of standard deviations in the precision studies (reproducibility and 
within-laboratory precision)  of the old and new systems should be either  
clinically and statistically insignificant,  or if statistically significant  it  should not  
be clinically significant.  (See Appendix II: Statistical Notes, 8).  
  26   Contains Nonbinding Recommendations  
	   The percentage of the observations over the entire range that fall within the ATD  
zone should be close to 95% with a lower limit of the 95% one-sided confidence 
interval higher than 90%.  The percentages of the observations that fall within the 
ATD zone for the low, medium,  and high ranges should approach 95% for each 
range.  (See Appendix  II: Statistical Notes,  11).   
    If applicable, the percent  of positive results by the  new system  among zero-level  
samples should be consistent with a Type I error of LoB of the old system  across 
three sites.  (Type I error is the probability of having True  Negative samples, i.e., 
those  with zero  analyte concentration,  give values that indicate the presence of  
analyte.   Usually, Type I error is set as 5% or less).  
    You should investigate any differences found between the two systems  and 
perform  a risk assessment to determine  what percentage of the intended use 
population would be affected by these  differences.  
C.   Migration  Studies for Semi-Quantitative  Assays  
Semi-quantitative assays are those which are neither qualitative nor quantitative.  An 
example of a semi-quantitative assay is one with a few ordinal categories (negative, trace, +, 
++, +++)  where  the order of categories contains information used during the  interpretation of  
the assay results.   Another example of  a semi-quantitative assay is an assay  which has  
continuous numeric  values but does not  have a  linearity property,  and,  therefore  is not  
quantitative.  The types of the analytical and comparison migration studies depend on the 
nature of the semi-quantitative assay.   If your semi-quantitative  assay has multiple cutoffs,  
the performance of the new  and old system  should be evaluated near  each cutoff separately 
(e.g.,  precision and systematic differences  at each cutoff).   You should contact the 
appropriate FDA  CDRH  or  CBER Division to obtain recommendations about migration 
studies for your particular semi-quantitative assay.  
D.   Migration  Studies for Point Of Care  (POC) Assays  
Before preparing to use the migration studies approach for a POC assay, you should 
determine whether the assay is quantitative, qualitative or semi-quantitative, according to the 
definitions in this guidance.  The migration studies should be conducted in the hands of  
intended users of the POC assays.  You  should contact the appropriate FDA  CDRH  or  CBER  
Division to obtain recommendations about migration studies  for a POC device.  
VII.  Other  Studies   
Depending upon the unique characteristics of the qualitative,  quantitative or semi-
quantitative assay being migrated to the new system, the following studies  may be called for.  
If not previously conducted for the old system, they should be performed for the new system. 
  27   Contains Nonbinding Recommendations  
If you determine that a study described below is not applicable for your system, you should  
describe your reasoning in detail in your application to FDA.  FDA will  consider such 
explanations  on a case-by-case basis particularly  for manual to semi-automated or  automated 
system  migrations.   
	   Carry-over or cross-contamination studies:  The importance of repeating these studies 
on a new system  can be ascertained by  a thorough analysis  of the new system.  As 
mentioned in  Section V  of this  document, block diagrams and side-by-side 
comparison tables would  be beneficial in this determination.   Changes to specific 
physical  features  such as a change in sample  pipettor design  or the layout of the new  
system  could  indicate the need for new  carry-over  studies.   If a  carry-over study for  
the new system  is appropriate  and the new design  is sufficiently similar to the old 
system, the new  study can be the same as  previously used for the old system.  
Samples with  high positive concentrations of analyte  should be tested  alternating with 
analyte-negative samples  in patterns dependent on the operational function of the 
instrument.  The concentration of analyte in the high positive samples  should  exceed  
95%-99%  or more of  the results normally obtained  in clinical  samples from  diseased 
patients in the intended use population.   This testing should be done over multiple 
runs (at least 5 runs are  recommended by the Commission of European 
Communities10).  
	   Matrix equivalency  and recovery studies:  Presumptively,  because there are no 
changes to the assay, there should be no new  effects  on the assay performance due to 
different matrices  unless physical alterations of the new system  could create such an 
effect. Similarly,  recovery studies  should not be affected by the migration of an assay 
from an old to a new system.  
	   Interfering substances studies:  Presumptively,  with  no changes to the assay,  there 
should be no new effects on the assay performance due to interfering substances.  
	   On-board reagent/calibrator and sample  stability studies: Unless there are physical or  
process changes to the new system,  presumptively,  there should be no effect  on assay 
performance due to  on-board reagent or  sample  stability.  
	   Cross-reactivity studies:  Presumptively, as there are  no changes  in assay components,  
a migration to a  new system  should  have no effect  on the existing cross-reactivity. 
	   Hook effect  studies: Presumptively,  because there is no assay change, the parameters 
of the hook effect should be the same,  unless physical alterations in  the new system  
could create such an effect.  
                                                           
10  Commission  Decision  2002/364/EC  of  7  May  2002  on  common  technical  specifications for  in  vitro-
diagnostic medical  devices [Official  Journal  L 131  of  16.05.2002].  
  28   Contains Nonbinding Recommendations  
	   Verification of kit  control material  and calibrators: Presumptively because there is no 
change  to the assay, the control results and calibration ranges should remain  the 
same, unless physical alterations in  the new system  could create new  effects.  
	   If new analyte-specific information requires new studies to bring the assays 

performance characteristics up-to-date, please contact FDA for guidance.  
 
VIII. Molecular  Assays  
There are specific criteria that  are  unique to nucleic acid  tests  (NAT)  and therefore NATs  
present additional specific  concerns  over serological  and antigen assays:  
	   When  appropriate,  you should provide  testing with  panels  showing a rise in viral titer  
over time from serial bleeds  (viremic profile).  Similar to seroconversion panels, they  
should have a minimum number of days between bleeds and begin with at least one 
negative bleed.  They should be of clinical relevance to the appropriate individual  
marker.  
	   Carryover studies:  Because of the increased risks of carryover due to the 
amplification methodologies utilized in molecular testing (e.g.,  PCR, TMA),  you 
should perform  carryover studies for  all  NAT migration studies.  
	   Sample  stability:  Because of the nature of DNA and especially RNA, careful attention 
should be given to the stability of  samples in relation to on-board storage and 
manipulation.  
	   Sample  processing:  The processes of  purification and extraction  of DNA or RNA  
from clinical  samples is critical to the success of  molecular tests.  You should 
evaluate any additions or  modifications  associated with the  new system  that  could 
affect these processes.  
	   Validation of  control material and calibrators:  You should perform these studies on 
the new system  due to the sensitive nature of molecular assays.  
	   For  molecular  assays detecting multiple analytes, please contact  FDA  for  further  
discussion.  
IX.   Regulatory Outcomes  
	   Should the acceptance criteria  noted in Sections  VI.A.4  or  VI.B.4  above  be  met, it  
would be appropriate for  the sponsor  to  claim that the new system  does not  
compromise the results as compared to the old system.  It would not be appropriate to  
claim improved  performance characteristics.  It would also not be appropriate  to 
compute clinical performance claims for  the new system  based on the migration 
  29   Contains Nonbinding Recommendations  
studies  described here, since these studies are analytical, rather than clinical.   Should 
you  wish to develop more extensive claims, the migration studies paradigm  would not  
be an appropriate scientific approach.  
	   If the acceptance criteria are not met  and  the aberrant performance could affect  
clinical management, you  will be asked to perform a complete clinical study 
presenting the clinical performance of the assay on the new system.  
X.   Glossary  
For the purposes of this document  the following definitions are  used.  HTD  referenced  terms 
are based on the CLSI Harmonized Terminology Database.  
C : a concentration at which repeated tests of  a  sample with this concentration under  
5
stipulated conditions are 95% negative (or  5% positive) (see CLSI EP12-A2).  
C : a concentration at which repeated tests of a sample with this concentration under  
95
stipulated conditions are 95% positive (see CLSI EP12-A2).  
C :  a concentration at which repeated tests of a sample with this concentration under  
50
stipulated conditions are 50 % positive (or 50% negative).  Under ideal circumstances, C
50  
will exactly equal the cutoff established by the manufacturer.   
Calibrators:  a substance or device that is based on a reference  preparation or in which the 
analyte concentration or other quantity has been determined by an analytical procedure of  
stated reliability.  Calibrators are used to calibrate, graduate, or adjust a measurement  [HTD].  
Carry-over: amount of analyte carried by the measuring system from one sample reaction 
into subsequent sample reactions, thereby erroneously affecting the apparent amounts in 
subsequent  samples  [HTD].  
Control material:  a device, solution, or preparation intended for use in the quality control  
process to monitor the reliability of a test system and to evaluate  its performance within 
established limits.   
Cross-reactivity: the ability of a  drug, metabolite, a structurally similar compound other  
than the primary analyte, or even unrelated compound to affect the assay  [HTD].  
Cutoff  value (CO): for a qualitative test, the threshold above which the result of the test is 
reported as positive and below which the result is reported as negative.   
High negative sample (C ): a sample with a concentration of analyte close to the C  as 
5 5 
determined by the old system.  This term is equivalent to a weak negative sample for  
example as used in the guidance document Recommendations for  CLIA Waiver  
Applications for Manufacturers of IVDs,  
http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDo 
cuments/ucm070890.pdf.   
Hook effect (high dose hook effect): effect  of a suboptimal antigen-antibody reaction in 
which either the antibody or antigen is in excess resulting in an incomplete, or blocked 
reaction  leading to  a decreasing signal response at very high levels of analyte.  It is used 
interchangeably with prozone effect,  [HTD].  
  30   Contains Nonbinding Recommendations  
Interfering substances:  endogenous (e.g., blood components, acidic polysaccharides) or  
exogenous (e.g., talc, anticoagulant) substances in clinical samples that can cause false-
positive or false-negative  results in a test system  [HTD].  
Limit of blank (LoB):  highest measurement result that is likely to be observed (with a stated 
probability) for a blank sample (a sample with concentration at or near zero) (CLSI EP17-A;  
[HTD]).  
Limit of detection (LoD):  the lowest concentration of analyte that can be reported to be 
present at a specified level of confidence, although perhaps not quantified to an exact value.  
Similarly, an amount of analyte in a sample for which the probability of falsely claiming the 
absence is  (type II error) given a probability  (type I error) of falsely claiming its presence  
(CLSI EP17-A;  [HTD])
   
Limit of quantitation  (LoQ):  the lowest amount of analyte in a sample that can  be 

quantitatively determined with {stated} acceptable precision and {stated, acceptable} 

accuracy, under stated experimental conditions (CLSI EP17-A;  [HTD]).
  
Linearity:  ability (within a given range) to provide results that are directly proportional to 

the concentration (amount) of the analyte in the test sample [HTD].
  
Linearity studies:  studies to determine the analyte concentration range over which the 

testing systems results are acceptably linear. 
  
Low positive sample (C ): a sample with a concentration of analyte close to C  as 

95 95 
determined by the old system.  This term is equivalent to weak positive sample for  
example as  used in the guidance  document  Recommendations for CLIA Waiver  
Applications for Manufacturers of IVDs,  
http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDo 
cuments/ucm070890.pdf.  
Measurand: particular quantity subject to measurement.  The term measurand and its 
definition encompass all quantities while the commonly used term analyte refers to a  
tangible entity subject to measurement  [HTD].   
Measuring interval (measuring range): set of values of measurands for which the error of a  
measuring instrument is intended to lie within specified limits.  The range of values (in units 
appropriate for the analyte [measurand]) over which the acceptability criteria for the method 
have been met; that is, where errors due to nonlinearity, imprecision, or other sources are  
within defined limits (CLSI EP06-A, [HTD]).  
Medical decision level (medical decision point): a level or concentration at which a test is 
interpreted for patient care and treatment.
	 
Moderate positive sample:  a sample with a concentration close enough to the cutoff and at
	 
which one can anticipate positive results  by the  old system  approximately 100% of the time.  
 
Negative percent agreement:  the proportion of samples negative by the  old system  for
	 
which the results by the  new system  are  negative (see FDA guidance  titled Statistical
	 
Guidance on Reporting Results from Studies Evaluating Diagnostic Tests  at
	 
  31   Contains Nonbinding Recommendations  
http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDo 
cuments/ucm071287.pdf).11  
New system:  an unapproved/unlicensed  system (assay, instrument, and software) to which 
the assay is migrating from a previously approved/licensed  system.  
Old system:  an approved/licensed  system (assay, instrument and software) from which the 
assay is migrating to a currently unapproved/unlicensed  system. 
 
Positive percent agreement: the proportion of samples positive by the old system  for which 

the results by the  new system  are positive.  (See FDA guidance  Statistical Guidance on 

Reporting Results from Studies Evaluating Diagnostic Tests, 

http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDo
	
cuments/ucm071287.pdf).
	 
Qualitative  assay:  assay in which  nominal properties of measurand  are identified.
	 
Quantitative  assay:  assay in which the amount or concentration of an analyte is measured 

and expressed as a  numeric  quantity value in appropriate measurement units.
	 
Repeatability:  closeness of the agreement between the results of successive measurements 

of the same measurand carried out under the same conditions of measurement  (See  CLSI	
 
EP05 [HTD]). 
	
Reproducibility:  closeness of  agreement between the results of measurements of the same 
	
measurand and carried out under changed conditions of measurement.  Reproducibility 

conditions are conditions where test results are obtained with the same method on identical
	 
test items in different laboratories with different operators using different equipment and can 

include additional variables such as days, replicates, and runs (See  CLSI EP05 [HTD]). 
	
Risk analysis:  systematic use of available  information to identify hazards and to estimate the
	 
risk.  Risk analysis includes examination of different sequences of events that can produce
	 
hazardous situations and harm  [HTD]. 
	
Semi-quantitative  assay:  assay  which is  neither qualitative nor quantitative  (such as an 

assay with a  few ordinal categories; negative, trace, +, ++, +++).
	 
Spiked sample:  a clinical sample to which exogenous analyte  has been added to create 
	
specified levels of signal.
	 
Systematic difference:  a mean of the measurand on the  new system  minus a value of the
	 
same measurand as performed on the  old system  that would result from an infinite number of 
	
measurements carried out under the stipulated condition (based on HTD). 
	
Within-laboratory precision:   precision over a defined time and operators, within the same
	 
facility and using the same equipment; calibration and reagents may vary.  Formerly, the
	 
term total precision  was used in CLSI EP05  [HTD].
	 
                                                           
11  The general  definition  from  the cited  guidance is adapted  in  this guidance since the cited  guidance refers to  
clinical  subjects,  whereas this guidance does not  involve subjects,  but  rather  specimens or  samples.   In  addition,  
the term  non-reference standard in  the cited  guidance is analogous to  old  system in  this guidance;  the term  
test in  the cited  guidance is analogous to  new  system.  
  32   Contains Nonbinding Recommendations  
XI.   FDA Guidance Documents and CLSI Guidelines 
Referenced  
1. 	  Quality System Information for Certain Premarket Application Reviews; Guidance 
for Industry and FDA Staff    issued 2003,  
http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocum 
ents/ucm070897.htm.  
2. 	  Guidance for Industry and FDA Staff: Replacement Reagent and Instrument Family 
Policy  issued 2003,    
http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocum 
ents/ucm079185.htm  
3. 	  Guidance for Industry and Staff:  Guidance for the Content of Premarket Submissions 
for Software Contained in Medical Devices  issued 2005,  
http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocum 
ents/ucm089543.htm.  
4. 	  Guidance for Industry and FDA Staff: Recommendations for Clinical Laboratory  
Improvement Amendments of 1988 (CLIA) Waiver Applications  for Manufacturers of  
In Vitro Diagnostic Devices  issued 2008,  
http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocum 
ents/ucm079632.htm.  
5. 	  Guidance for Industry and FDA Staff: Statistical Guidance on Reporting Results from  
Studies Evaluating Diagnostic Tests  issued 2007,  
http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocum 
ents/ucm071148.htm.   
Clinical and Laboratory Standards Institute  (CLSI)  documents:  
1. 	  CLSI.  Evaluation of Precision Performance of Quantitative Measurement Methods;  
Approved GuidelineSecond Edition.  CLSI document  EP05-A2.  Wayne, PA:  
Clinical and Laboratory Standards Institute;  2004.  
2. 	  CLSI.  Evaluation of the Linearity of Quantitative Measurement Procedures: A  
Statistical Approach; Approved Guideline. CLSI document  EP06-A.  Wayne, PA:  
Clinical and Laboratory Standards Institute, 2003.  
3.	   CLSI.  Method Comparison and Bias Estimation Using Patient Samples; Approved 
Guideline   Second Edition  (Interim Revision). CLSI document  EP09-A2-IR.   
Wayne, PA: Clinical and Laboratory Standards Institute, 2010.  
4.	   CLSI.  User Protocol for Evaluation of Qualitative Test Performance; Approved 
Guideline-Second Edition.  CLSI document  EP12-A2.  Wayne, PA: Clinical and 
Laboratory Standards Institute; 2008.  
5.	   CLSI.  User Verification of Performance for Precision and Trueness; Approved 
Guideline   Second Edition. CLSI document  EP15-A2.  Wayne, PA: Clinical and 
Laboratory Standards Institute;  2006.  
  33   Contains Nonbinding Recommendations  
6.	   CLSI.  Evaluation of Detection Capability for Clinical Laboratory Measurement  
Procedures; Approved Guideline    Second Edition. CLSI document  EP17-A2.  
Wayne, PA: Clinical and Laboratory Standards Institute;  2012.  
7. 	  CLSI.  Estimation of Total Analytical Error for Clinical Laboratory Methods;  
Approved Guideline. CLSI document  EP21-A.  Wayne, PA: Clinical and Laboratory 
Standards Institute, 2003.  
  34   Contains Nonbinding Recommendations  
Appendix I  - Migration Studies for Blood Donor  Screening 
Assays12  
1. Introduction  
Blood Donor  Screening Assays for infectious agents,  reviewed under  Biologics License 
Applications  (BLA),  are generally held to stringent  standards of sensitivity and specificity.  
Typically, clinical studies for licensure of products such as HIV assays involve testing of  
over 1000 known positives and  6000 to 10,000 low risk individual  samples (or pools)  
collected from the intended use population.  Consequently, FDA recommends larger study 
sizes for migrating blood screening assays to new systems.  
Otherwise, except as specifically noted below, the same considerations apply to blood 
screening assays as described  for qualitative assays in Section VI.A of this document, 
Migration Studies for Qualitative Assays.  
a. Performance  at Low Analyte Levels  
For immunoassays, FDA recommends that at least 20 seroconversion panels, or as many 
as are available (whichever is less) be studied, comparing the new and the old systems 
head to head.  For  nucleic acid tests (NAT), FDA recommends the head-to-head testing 
of as many seroconversion panels as were tested for licensure of the old system  (typically 
10).  Both qualitative results and  numeric signal  (e.g.  signal output, S/CO ratios)  should 
be compared.  
b. Precision  Study (Within-Laboratory Precision)
  
FDA recommends that sponsors compare the new and old systems in a Precision Study as 

outlined in Section VI.A.1.b. 
  
c. Reproducibility  Study  
FDA recommends that sponsors compare the new and old systems in a Reproducibility 
Study essentially as outlined in Section VI.A.1.b.iii.   However, FDA recommends 
including in the panel at least one truly negative sample  (i.e. not just  a positive sample  
diluted to below the cutoff), and that testing be performed at three sites, one of which 
may be in-house.  
2. Comparison Panels  
a. Positive Panel Members  
A positive comparison panel should consist of approximately 100 positive samples, to 
include 60-80  specimens  with signals <3X the cutoff for an immunoassay or analyte 
concentrations <3X the 95% LoD for a NAT.  Authentic clinical specimens are preferred:  
however, specimens may be diluted to  the recommended range in negative matrices  
(individual, not pooled)  if  clinical  specimens are not  available.  The panel should be 
tested on the new system  at three sites, one of which can be in-house.  This panel should 
                                                           
12  Appendix  1  does not  apply  to  immunohematology  tests licensed  by  CBER.  
  35   Contains Nonbinding Recommendations  
also be tested at least once on the old system  (this can be in-house).  We recommend use 
of at  least two of the old systems to better assess systematic differences between old 
systems.  The data should be analyzed by S/CO regression and analysis of bias using 
scatter-plots or similar graphical presentations, as described in Section VI.A.3.c.  
b. Negative Panel Members  
Option 1:   A negative comparison panel should consist of 3000 known negative samples 
(or pools), or specimens obtained from a low risk study, with adequate follow-up.  The 
panel should be tested on the new system, distributed over three  sites, one of which may 
be in-house (e.g., 1/3 at site one, 1/3 at site two & 1/3 at site three).  The data should be 
analyzed for agreement of the point estimate of specificity (with the 95% confidence 
interval) for the new system  with the original point  estimate of specificity (with the 95%  
confidence interval) from the original trial of the old system.  
Option 2:   As an alternative option, the sponsor may wish to test head to head on the old 
and new systems at three external sites the highest 10% of negative specimens from the 
original clinical trial of the assay on the old system, if the specimens have been stored 
under conditions defined in the instructions for use of the assay.  
3. Acceptance Criteria  
Except as noted above, the same acceptance criteria as recommended in Section VI.A.4 also  
apply to blood donor  screening assays.  
Additionally, sponsors may recommend statistical analysis protocols based on estimating 
false positive and false negative ratios from the negative and positive comparison panel  
studies, respectively.  Sponsors interested in this approach should determine an appropriate 
model for the S/CO distribution of each panel (positive or negative) together with a proposed 
method of analysis.  
4. Interfering Substances and Conditions  
Only substances and conditions that represent a reasonable risk of interference in the new  
system  should be studied.  For instance, interfering conditions such as hemolysis or  
hyperlipidemia might influence pipetting or washing steps and should be included in 
migration studies.  Conversely, it would seem unlikely that cross-reactivity of, for instance, 
an HIV NAT assay with HTLV would likely be influenced by migration to a new system.  
Each interfering substance/condition may be tested in-house using a panel of approximately 
10 Low  Positives with signals <3X the cutoff  for an immunoassay or analyte concentrations 
<3X the 95% LoD for a NAT.  (These studies can be performed by spiking the analyte at the 
level described above in  negative specimens (for the analyte) with interfering 
substances/conditions).   
Each interfering substance/condition may be tested in-house using a panel of approximately 
10 True Negatives.  
Because migration studies extend the life of individual assays and new information becomes 
available over time, it is important to update the performance characteristics of the assay 
during migration of the assay.  Based on the type of data considered for the original assay, 
  36   Contains Nonbinding Recommendations  
examples of new information that may trigger additional study are newly recognized 
potentially interfering substances or conditions,  or new variants,  or new recombinants.    
Appendix II  - Statistical Notes  
1.  Evaluation of  C  and C  using Precision  Studies  
5  95 
Consider that an assay (qualitative or  quantitative) has a  numeric  output  in which higher  
values indicate higher levels of the analyte and analytical variation about the C  is 
50 
approximately normal (or approximately normal after appropriate transformation).  If the 
standard deviations (SD) in the precision studies of the old system  for  concentrations around 
the cutoff  value are almost constant, then:  
C  = C  +1.645 x SD,  and  
95  50 
C  = C    1.645 x SD  
5  50 
For example, if the cutoff for  optical density (OD)  value is 1.00 and the SD around the cutoff  
is approximately 0.10, then C  is approximately 1.16  OD  (=1.00+1.645 x 0.10)  and C is 
95  5  
approximately 0.84  OD  (=1.00 -1.645 x 0.10).  In other words, a sample with  an  actual  OD  
of 1.16 produces positive results (above  1.00) approximately 95% of the time and a sample 
with an actual  OD  of 0.84 produces negative results (below 1.00) approximately 95% of the 
time.  
If the coefficient of variation (CV) in the precision studies of the old system  for  
concentrations around the cutoff  value are almost constant, then  
C  = C  + 1.645 x CV x C  and C  = C    1.645 x CV x C . From here,  
95  50  95  5  50  5
C  = C  / (1   1.645 x CV) and  
95  50 
C  = C  / (1 + 1.645 x CV).   
5  50 
For example, if the cutoff  has an OD  value of  1.00 and the %CV around the cutoff  is 
approximately 10% (i.e., CV=0.10), then C  is approximately 1.20 OD  and C is 
95  5  
approximately 0.86  OD.  
If the limit of blank (LoB) is used as a cutoff, then the concentration C  is the same as  the  
95 
limit of detection (LoD) and zero concentration is C (see CLSI EP17).  
5  
2.   Calculating  Confidence Interval for the Ratio of the Standard Deviations  
Let 2  and 2  be true variances and SD2 and SD2  be estimated variances. Consider  
New  Old  New   Old 
the expression F = [SD2 / 2  ] / [SD2 / 2  ] which follows an F distribution with 
New New  Old Old 
degrees of freedom df=  (numerator) and df=  (denominator): F(1, 2).13   For a level of  
1  2 
confidence , let F(1-/2, 1, 2) and F(/2, 1, 2) be critical values that  
Prob  {F(/2,  ,  ) <[SD2 / 2  ] / [SD2 / 2  ] <  F(1-/2,  ,  )} = 1-;   
1 2 New New  Old Old  1 2
                                                           
13  For  more details see Searle S.R.,  Cassella G.  and  McCullagh  C.E.  Variance Components (1992)  
Wiley&Sons;  Hahn  G.J.,  Meeker  W.Q.  Statistical  Intervals.  A  Guide for  Practitioners  (1991)  Wiley&Sons.    
  37   Contains Nonbinding Recommendations  
  Prob {(1/F(1-/2,  ,  )) * (SD2  / SD2  ) < 2  / 2   < (1/F(/2,  ,  )) * 
1 2 New  Old  New  Old  1 2
(SD2  / SD2  )} = 1-;  
New  Old 
Therefore,  the  interval from (1/F(1-/2,  ,  )) * (SD2  / SD2  ) to (1/F(/2, 1,  )) * 
1 2 New  Old  2
(SD2  / SD2  }is a two-sided 95% confidence interval for  2  / 2  . To find a  
New  Old  New  Old 
confidence interval for the ratio of standard deviations   /  , take square roots.  Note  
New  Old
that the F distribution has the property that F(1-/2,  ,  ) = 1/F(/2,  ,  ).  
1 2 2 1
For determination of degrees of freedom, you should refer to  CLSI EP05.  For example, for  a  
precision study conducted with 3 sites, 5 days per site, 2 runs per day and 3 replicates per  
run, the estimate of SD of repeatability for one run has 2 degrees of freedom (=3-1) and the  
estimate of SD of repeatability for all  thirty (=3*5*2)  runs has 60 degrees of freedom  
(=3*5*2*2).   
3.	  D  eming and Passing-Bablok Regressions  
Ordinary least squares regression analysis supposes that one of the methods is without  
random measurement error,  and the standard deviation of the error distribution of the other  
method is constant through the measurement range.  An assumption about  the  absence of  a  
random measurement error is not fulfilled in the migration comparison study data because  
both methods, X and Y, are subject to random measurement errors; therefore, Deming and/or  
Passing-Bablok regression analyses are recommended.  An assumption  of a  constant standard 
deviation of X and Y methods through the  entire measurement range does not hold for most  
of the assays.  For example, very frequently, the standard deviation increases as the  
concentrations increases.  In situations like this, weighted Deming regression can often be  
used.  
The analysis of the  numeric  values in the migration comparison study data should include an 
appropriate type of Deming regression (e.g., weighted) for each site separately and for all  
sites combined.   
To apply a Passing-Bablok regression analysis, the comparison study data should adhere to 
the following requirements: CV  / CV  =  where  = the slope (it is assumed that X and Y  
Y  X 
have approximately the same random measurement errors).  In an article by Passing, H. and 
Bablok, W.14,  the authors performed simulations to investigate how inequality in the random  
measurement error of X  and Y  affects Passing-Bablok regression.  The authors found that if  
0.67<CV /CV <1.5 then Passing-Bablok regression is acceptable.  If  1.5<CV /CV  <2.5 
Y X   Y X 
(or 0.4<CV /CV <0.67)  and precision of X  is less than 7% then Passing-Bablok regression 
Y X
is  acceptable.   
When applying regression analysis of study data for all sites combined, note that only one  
measurement per sample is reported from the  old system  (X data), while an  average of three  
measurements (one per study site) is reported for the  new system  (Y data).  In the case of  
combined data, the  CV of  the  average of Y is less because the average of Y is more precise  
                                                           
14  Passing,  H.  and  Bablok,  W.14  Comparison  of  Several  Regression  Procedures for  Method  Comparison  
Studies and  Determination  of  Sample Sizes in  J.  Clin.  Chem.  Clin.  Biochem.,  Vol.  22,  1984,  pp.431-445,  
  38   Contains Nonbinding Recommendations  
than one measurement of Y.  So, when combining data from all sites, the CV of  the average 
of   the Y  measurements is calculated as the standard deviation of the Y data divided by the 
square root of 3 (CV of average Y = CV  * 0.58).  
Y 
In addition to the Deming regression, you could also include  Passing-Bablok regression 
analysis for each site separately.  If the precision of X  is less than 7% then, in addition to the 
Deming regression analysis for the combined data, present Passing-Bablok regression 
analysis for the combined data.  
4.  Examples  of Data Tables  for Qualitative Assays   
The following are examples of detailed tables of agreements  referred  to above within Section 
VI.A.3.c-Comparison Panels (for Qualitative Assays).  
Positive panel samples:  
Old  System Positive  
Low Positive   Moderate  Positive   High  Positive  
(close to C )  
95
New System Positive   27   30   40  
New System Negative   3  
Total   30   30   40  
Negative panel samples:   
Old System Negative  
Low  and Moderate Negative   High Negative  
(close to C )  
5
New System Positive   3  
New System Negative   70   27  
Total   70   30  
If the CO  of the assay is the LoB, the columns of  Low  Negative and Moderate Negative can 
be combined  as in the example above.    
 
 
 
Table of agreement 2-by-2:  
Old System  
Negative   Positive  
New System   Negative   A   B  
1  1 
Positive   A   B  
2  2 
Total   N   N  
A  B 
  39   Contains Nonbinding Recommendations  
   Calculate  Negative Percent Agreement (NPA) as A /N  with 95% two-sided CI;  
1 A 
   Calculate  Positive  Percent Agreement (PPA) as B /N  with 95% two-sided CI;  
2 B 
5. Examples of Data Tables for Qualitative Assays  with Equivocal (and/or Re-testing 
Zone) Results.  
Examples  of tables for  an  assay with an equivocal zone  of  0.8-1.2 S/CO is provided below  
(E =0.8 S/CO and E =1.2 S/CO).  
1 2
Detailed tables of agreement:  
Old System  
Negative   Equivocal   Positive  
Strong  Close to  0.80-1.20   Close to  Strong and 
and  C  of E   C  of E   moderate 
5  1  95  2 
moderate  positive  
negative  
Negative   X   X   X  
New  
Equivocal   X   X   X  
System  
Positive   X   X   X  
Total   70   60   70  
 
Old System  
Negative   Equivocal   Positive  
New System   Negative   A   B   C  
1  1  1 
Equivocal   A   B   C  
2  2  2 
Positive   A   B   C  
3  3  3 
Total   N   N   N  
A  B  C 
   Calculate  Negative Percent Agreement (NPA) as A /N  with 95% two-sided CI;  
1 A 
   Calculate  Positive Percent Agreement (PPA) as C /N with 95% two-sided CI;  
3 C 
   Calculate  percents of negative, equivocal and positive results by the new system  
among N  equivocal results by the old system.  
B 
In addition, an example  of  more detailed information about  PPA and NPA  is  shown  in the 
format  below:  
  40   Contains Nonbinding Recommendations  
    Percent  95% CI 
Negative Percent  All samples negative     
Agreement  by the Old system  
Negative samples     
below C  
5 
Positive Percent  All samples positive     
Agreement  by the Old System  
Positive samples     
above C  
95 
Equivocal  Provide numbers and percents of equivocal, negative and positive 
results by the New System.  
 
 
6. Calculating Score Confidence Intervals for Percentages and Proportions 
The following are additional recommendations for performing statistical analyses of 
percentages or proportions. Confidence limits for positive percent agreement and negative 
percent agreement can be calculated using formulas for calculating a confidence interval for 
a binomial proportion.  There are several different methods available.  We suggest that either 
a score method described by Altman, et al. (Altman D.A., Machin D., Bryant T.N., Gardner 
M.J. eds. Statistics with Confidence. 2nd ed. British Medical Journal; 2000) or a Clopper-
Pearson Method (Clopper CJ, Pearson E. Biometrika 1934; 26:404-413) be used. 
An advantage with the score method is that it has better statistical properties and it can be 
calculated directly. So with n=100 samples and 96/100=96% agreement, the score lower 
confidence bound is 90.2% whereas the Clopper-Pearson lower confidence bound is 90.1%. 
In this document, we have illustrated the reporting of confidence intervals using the score 
approach. For convenience, we provide the formulas for the score confidence interval for a 
percentage. Note that the lower bound of a two-sided 95% score confidence interval is the 
same as the lower bound of a one-sided 97.5% score confidence interval; and the lower 
bound of one-sided 95% score confidence interval is the same as the lower bound of a two-
sided 90% score confidence interval. 
A two-sided 95% score confidence interval for the proportion of A/B is calculated as: 
       
100% Q  Q  / Q ,100% Q   Q  / Q , where the quantities Q , Q , and Q  are
1 2 3  1 2  3  1 2 3
computed from the data using the formulas below.  For the proportion of A/B: 
Q  2  A  1.962  2  A  3.84  
1 
  41  Contains Nonbinding Recommendations  
Q 1.96  1.962  4  A  (B  A)/ B  1.96  3.84  4  A  (B  A)/ B  
2 
Q 2  (B 1.962)  2  B  7.68  
3 
 
In the formulas above, 1.96 is the quantile from the standard normal distribution that 
corresponds to 95% confidence. For calculation of 95% one-sided score confidence interval, 
use 1.645 in place of 1.96 in the formulas above. 
7.  Allowable Total Difference For Qualitative Assays with Equivocal (and/or Re-testing 
Zone) Results 
Based on the reproducibility of the old system for the samples close to the zone of equivocal 
results (and/or the re-test zone), you can establish an allowable total difference zone as 
presented in Figure 8 below where E  and E  are the cutoffs for the zone of equivocal results. 
1 2
In Figure 8, r is a result of one measurement for a sample with a result below the cut-off E  
1 
and repeated measurements are below E  with high probability; likewise R is a result of one 
1
measurement for a sample with a result above the cut-off E  and repeated measurements are 
2
above E  with high probability. 
2
 
  42  Contains Nonbinding Recommendations  
Figure 8. Allowable total difference zones for a qualitative assay with equivocal 
results. Light gray: Negative results by New System, Medium gray: Equivocal 
results by New System, Dark gray: Positive results by New System 
You should calculate the percentages of the samples with Negative, Equivocal, and 
Positive results by the new system that fall within the five concentration ranges defined 
by the old system: below r, r-E , E -E , E -R, above R. 
1 1 2 2
 
8. Relationship between Clinical and Statistical Significance 
 
Observed Difference  Observed Difference  Interpretation 
From Clinical Point of  From Statistical Point of 
View  View 
Not-significant  Not-significant  Acceptable1 
Not-significant  Significant  Acceptable1 
Significant  Not-Significant  Additional data are likely 
needed2 
Significant  Significant  Not acceptable 
1Confidence interval is within clinically acceptable differences 
2Confidence intervals too wide to reach a conclusion 
9. Acceptance Criteria for Positive and Negative Percent Agreements. 
For a panel of 100 samples which test positive by the old system, and of which 96 also test 
positive by the new system (96 out of 100), the lower limit of the 95% two-sided score 
confidence interval is above 90%. For 30 samples with values close to C , the 95% two-
95
sided confidence interval for 26/30 (87%) is 70.3% to 94.7%. If, for example, among the 30 
samples with low positive concentrations (concentrations close to C  by the old system), 
95
only 25 samples test positive by the new system, then the percent of positive results by the 
new system for the samples close to the cutoff is statistically different from 95% (83% 
(25/30) with 95% CI: 66.4% to 92.7%). It should be noted that if the percent agreement is 
96% or higher at each of three sites, then the lower confidence bound exceeds 90% and a 
formal calculation of the 95% lower confidence bound may not be needed.  The lower bound 
of the confidence interval for overall agreement is bigger than the smallest of the lower 
bounds calculated at each site and may be used to demonstrate that the agreement criteria has 
been met.  
10.  Calculation of Allowable Total Difference 
For each sample of the Comparison panel, calculate the differences between the new system  
result (Y) and the old system result (X), Y-X (based on CLSI EP21).  Also calculate (X+Y)/2.  
Plot the difference between Y and X, Y-X, against their mean (Y+X)/2 (Bland-Altman plot)15. 
                                                           
15  See Bland J.M. and Altman D.G. Measuring agreement in method comparison studies, Statistical Methods 
in Medical Research 1999; 8; p.135-160.   
  43  Contains Nonbinding Recommendations  
On the Bland-Altman plot of (Y-X) vs. (Y+X)/2, provide the Allowable Total Difference 
(ATD) zone around the axis, (Y+X)/2. The ATD zone is established in such a way that 95% 
of differences between the old system result and the repeated result by the old system fall 
within the ATD.  The ATD zone is expressed as: 
 1.96  2  CV(Y+X)/2 =  2.77CV(Y+X)/2 for larger values of old system and  
1.96  2 SD =  2.77SD for the low values of old system where CV and SD are the 
reproducibility characteristics of the old system (see Establishing SD and percent CV for ATD 
Based on the Performance of the old system below). A hypothetical example of the ATD 
zone on the Bland-Altman plot is provided below (Figure 9): 
  44  Contains Nonbinding Recommendations  
 
 
+1.96  2 CV(Y+X)/2 
+1.96  2 SD 
ATD 
-1.96  2 SD 
-1.96  2 CV (Y+X)/2 
 
 
Figure 9. A hypothetical example of the ATD zone on the Bland-Altman plot is 
provided below.  
By the appropriate transformation, a similar ATD zone can be presented on the plane of new 
system values (Y) against old system values (X), see Figure 7.  The expressions of the lines 
of the ATD zone on the plane Y vs. X are the following: 
Lines parallel to the diagonal of the ATD zone: 
Y  X 1.96   2 SD =X  2.77  SD, if  0  Y+X  2  A  
 
For CV10% and when each sample in the comparison panel is measured one time by the old 
system, lines for the expanding part of the ATD zone are: 
1.96  2 CV  2.77 CV
Y  X (1  )  X (1   )
11.96  2 CV /2    11.39C V 
 
1.96  2 CV  2.77 CV
Y  X (1   )  X (1   )    if Y+X>2  A 
11.96  2 CV /2    11.39C V 
where A is SD/CV. 
 
  45  Contains Nonbinding Recommendations  
For CV>0.10 or when each sample is measured more than one time by the old system, an 
approach based on a ratio of two normal variables is recommended.16  Examples of ATD 
lines for CV0.10, and when each sample is measured one time by the old system is 
presented in table below: 
 
  Allowable Total Difference Zone 
Line  =A *X and Line  =A *X 
1 1 2 2
CV  A  A  
1 2 
0.10  0.75  1.32 
0.15  0.65  1.54 
0.20  0.55  1.81 
  
Establishing SD and percent CV for ATD Based on the Performance of the Old System 
For an individual measurement X of a given sample by the old system, there is a following 
i
expression: X = X  + Mean-Bias + Random-Bias + where deviation of X from the true 
i truei i i  i
value X  is composed of a mean bias, a random matrix-related interference component, and 
truei
a random measurement error17,18. Because there are no changes in the assay, it is anticipated 
that the random matrix- related interferences in both systems are the same.  Then the 
difference between new system and old system measurements of the same sample depends 
on a random measurement error. 
Establishing standard deviation (SD) for the Allowable Total Difference (ATD) zone should 
be based on consideration of possible variance between the two measurements of the same  
sample by the old system obtained at different sites.  For this, consider the precision profile 
of the reproducibility study with the between-site component of variance.  Another 
hypothetical precision experiment for the old system can produce a slightly higher SD than in 
this precision experiment.  In order to address this, the observed SD may be multiplied by the 
appropriate factor (factor =(1  1/(4  f )) 1  f  2 ( f ), f  is a degree of freedom of the 
5% 
estimated SD).  
For example, if the degrees of freedom of the SD in the precision study of the old system  
were 40, then the appropriate factor is 1.236 and the expected maximum observed SD can be 
as high as 0.148 (=0.120 *1.236). After the appropriate SD or percent CV is established for 
each concentration in the precision study, the ATD zone can be obtained by smooth 
interpolation. 
                                                           
16  Zhang L., Mathew T., Yang H., K. Krishnamoorthy, Iksung Cho I. (2009): Tolerance Limits for a Ratio of 

Normal Random Variables, Journal of Biopharmaceutical Statistics, 20:1, 172-184. 

17  Krouwer JS. Estimating total analytical error and its  sources.  Techniques to improve method evaluation.  

Arch. Pathol. Lab. Med. 1992; 116:726-731. 

18  Linnet K. Boyd JC. Analytical validation of methods  With statistical methods.  In: Burtis C, Ashwood ER, 

Bruns D (eds) Tietz Textbook of Clinical Chemistry and Molecular Diagnostics. 4 ed. New York: Saunders, 

2006, p.353-407
  
  46  Contains Nonbinding Recommendations  
11. Number of Samples in the Allowable Total Difference Zones 
For 150 samples with 95% of the observations (143 /150) falling in the ATD zone, the lower 
limit of the 95% one-sided confidence interval is above 90%.  
  47