IGF-1 lab platform reference range divergence

IGF-1 is the central laboratory readout for every pharmacology that operates on the growth-hormone axis — Sermorelin, Tesamorelin, CJC-1295, Ipamorelin, MK-677, Hexarelin, GHRP-2, Anamorelin, recombinant somatropin, and the engineered analogs IGF-1 LR3 and similar. The peptide-user community has converged, correctly, on serial IGF-1 measurement as the closest available proxy for whether a cycle is producing pharmacology in the expected direction. What the community converges on less reliably is that the number reported on a commercial laboratory report is not a property of the patient's serum alone — it is a property of the patient's serum measured on a specific platform with a specific antibody pair and a specific calibration history. The same sample, drawn at one venipuncture and aliquoted into multiple tubes, returns systematically different values from Roche, Siemens, IDS, DiaSorin, and Mediagnost. The literature documenting this divergence is large, consistent, and largely unread outside the clinical-laboratory and acromegaly-management communities.

The operational consequence for a biohacker on a GH-secretagogue cycle: an IGF-1 value of 220 ng/mL at one lab and 280 ng/mL at another may represent identical underlying pharmacology measured on two non-equivalent platforms. The peptide cycle may have moved the marker, the platforms may have moved the marker, or some combination. Without same-platform measurement at both timepoints, the data does not distinguish the cases. This reference dossier documents what the published platform-comparison literature shows, what the available standardization efforts have and have not achieved, and how a self-experimenter tracking the GH-axis target marker should structure measurement to produce interpretable serial data.

The companion practice-level guidance lives in the biomarker monitoring guide for peptide users; the receptor pharmacology background sits in the GH-axis dossier; the discontinuation-trajectory context is in the GH-secretagogue discontinuation playbook. This page is the methodological reference the others assume.

Why this matters for peptide users

The peptide field's central monitoring claim — measure IGF-1 before, during, and after a GH-axis cycle to characterize the pharmacological effect — depends on the assumption that the measurements at the three timepoints are comparable. When all three draws happen at the same lab vendor on the same platform, the comparison is reasonable. When the draws happen at different vendors, or when the same vendor changes platforms (which occurs more often than the patient knows), the comparison is between numbers measured on different scales. The pharmacological signal and the analytical drift are confounded.

A worked example anchors the framing. A 42-year-old user begins an Ipamorelin and CJC-1295 protocol in March 2026; the baseline draw at one clinic returns IGF-1 = 175 ng/mL, and the six-week follow-up draw at a different clinic returns 220 ng/mL. The naive interpretation is a 26% pharmacological rise. The methodologically careful interpretation: the apparent 26% delta combines the actual pharmacological effect with the platform-attributable bias between the two labs' assays, and the published comparison literature documents that the platform bias term alone can be 25-40% in either direction between commercial assays on identical samples (Lee et al., Clin Chim Acta 2023, 539:1-7; Chanson et al., J Clin Endocrinol Metab 2016, 101:3450-3458). The pharmacological term is not separable from the platform term in this dataset.

The problem is more acute for biohacker monitoring than for routine clinical use because the populations differ. A clinician evaluating an acromegaly patient typically uses the same lab repeatedly; the platform drift is held constant across measurements, and the comparison to the platform-specific reference range is internally consistent. A biohacker drawing at convenient clinics across multiple states, switching between direct-to-consumer panel vendors, or comparing personal values to internet-circulated "youthful target" numbers from unspecified sources is operating in the regime where platform variation dominates the signal.

The five major commercial IGF-1 platforms

The published literature on IGF-1 platform comparison consistently focuses on five chemistries that account for the majority of commercial IGF-1 measurement worldwide. The fifth, Mediagnost, is largely a research and reference platform; the other four cover most commercial clinical lab volume across North America and Europe.

Roche Elecsys IGF-1 (electrochemiluminescence)

The Roche Elecsys IGF-1 assay is an electrochemiluminescence immunoassay (ECLIA) running on the Cobas e-platform line, with calibration against the WHO 1st International Standard for IGF-1 (preparation 02/254), the consensus calibrant adopted across the field after the 2008 WHO Expert Committee on Biological Standardization assignment (Burns et al., Growth Horm IGF Res 2009, 19:457-462). The platform's sample type is serum; intra-assay coefficient of variation sits below 10% per the manufacturer's performance documentation. The Roche platform is widely deployed across hospital labs and several large reference laboratories in the U.S. and Europe.

In published platform comparisons against LC-MS reference methods, the Roche Elecsys reads modestly lower than the LC-MS reference, with the Mohammed-Ali et al. Clin Biochem 2022, 108:14-19 Mayo Clinic comparison documenting Roche values as the reference point against which the DiaSorin assay showed a 24% positive bias and a 29% positive bias relative to LC-MS. The same paper documents that the DiaSorin assay produces nine of forty-three samples falsely elevated above its reference range when compared to clinical acromegaly classification anchored on the LC-MS method — the platform-bias problem is not abstract; it produces real misclassification in clinical decision-making.

Siemens IMMULITE 2000 (chemiluminescent solid-phase)

The Siemens IMMULITE 2000 IGF-1 is a chemiluminescent solid-phase immunometric assay that has been one of the most-used IGF-1 platforms in U.S. commercial laboratories for the past two decades. The calibration history is informative: the IMMULITE assay was calibrated against the earlier International Reference Reagent 87/518 until April 2017, then transitioned to the WHO 02/254 standard in May 2017. The transition itself shifted the absolute values reported on the platform — a worked illustration of the broader point that "the platform's calibration" is not a fixed property even within a single platform across time.

The IMMULITE platform reads, in head-to-head comparison, systematically lower than the IDS iSYS platform on identical samples; the Lee et al. 2023 paper documents the IMMULITE result averaging 36% lower than the DiaSorin LIAISON XL value on 110 paired specimens, with the IDS iSYS reading 81% higher than the IMMULITE on the same samples. The magnitudes of bias are large enough that the same patient sample crosses the upper-limit-of-normal threshold on one platform but not another in a measurable fraction of cases.

IDS iSYS (chemiluminescent automated)

The Immunodiagnostic Systems iSYS IGF-1 assay is a chemiluminescent automated immunoassay calibrated against WHO 02/254 (Bidlingmaier et al., J Clin Endocrinol Metab 2014, 99:1712-1721). The platform was developed in part by the same consortium that established the modern multicenter reference-interval dataset; the 15,014-subject Bidlingmaier dataset was generated on the iSYS platform and remains the largest published age- and sex-stratified IGF-1 reference dataset in the literature. The iSYS platform is widely used across European clinical laboratories and has become the U.S. LabCorp default IGF-1 method for several of LabCorp's IGF-1 test codes, including the IDS-iSYS-based 010540 IGF-1 With Z Score offering.

The Bidlingmaier 2014 dataset is the closest thing the field has to a contemporary cross-population reference; the corrigendum published in 2020 (J Clin Endocrinol Metab 105:e4983) corrected the published SD-score calculation formula but did not change the underlying age- and sex-stratified intervals. Comparisons between iSYS and the Mediagnost RIA reference method document broad agreement without significant bias (Chanson et al. 2016), which is part of why the iSYS-derived reference intervals have been adopted in much of the modern acromegaly-management literature.

DiaSorin LIAISON XL (chemiluminescent automated)

The DiaSorin LIAISON XL IGF-1 assay is a chemiluminescent automated immunoassay that, in the platform-comparison literature, sits at the high end of the IGF-1 measurement range — systematically reporting higher values than Roche Elecsys, LC-MS reference methods, and the Mediagnost RIA on identical samples. The Mohammed-Ali 2022 Mayo Clinic dataset documented the DiaSorin platform at a 24% positive bias relative to Roche Elecsys and 29% positive bias relative to LC-MS. The clinical consequence reported in that paper: even though the DiaSorin platform's reference range is set higher than the Roche or LC-MS ranges, the platform-specific upper-limit-of-normal threshold does not fully compensate for the upward bias, producing a measurable rate of false-positive acromegaly classifications.

Mediagnost RIA / IRMA / ELISA (research and reference)

Mediagnost GmbH manufactures the IGF-1 RIA, IRMA, and ELISA kits that have historically anchored the academic and reference-laboratory literature on IGF-1. The Mediagnost RIA in particular has been used as a comparison method in many of the published platform-comparison studies, and the Mediagnost ELISA appears in the multicenter Chanson 2016 study as one of the six immunoassays evaluated against ~900 healthy adult serum samples. The Mediagnost methods are less commonly deployed in U.S. commercial clinical laboratories — clinicians and members will more often see Roche, Siemens, IDS, or DiaSorin on a commercial report — but the Mediagnost results form a substantial fraction of the academic IGF-1 literature that biohackers reference when comparing their values to "published normal ranges."

The Chanson 2016 multicenter comparison documented that the iSYS and Mediagnost RIA were in good overall agreement (no significant bias by Bland-Altman analysis), while the DiaSorin LIAISON XL and Mediagnost RIA did not agree well. The clinical-laboratory community has tended to anchor on Mediagnost-RIA-equivalent calibration when evaluating other platforms' performance because the Mediagnost methodology has the longest comparison history with mass-spectrometry-based reference measurement.

Beckman Coulter Access (less prominent for IGF-1)

The Beckman Coulter Access / DxI line is a major immunoassay analyzer platform broadly deployed across clinical laboratories, but Beckman is less prominently featured in the IGF-1 platform-comparison literature than Roche, Siemens, IDS, DiaSorin, or Mediagnost. The published platform-comparison studies that anchor this dossier (Bidlingmaier 2014, Chanson 2016, Lee 2023, Mohammed-Ali 2022) primarily compare the four immunoassay platforms above against the Mediagnost reference and LC-MS reference methods. A member receiving an IGF-1 result on a Beckman platform will need the local laboratory's method statement to determine the platform-specific reference range; the cross-platform conversion literature does not extensively cover this assay relative to the others.

Why the same sample reads differently across platforms

The IGF-1 molecule is a 70-amino-acid single-chain polypeptide that circulates in serum almost entirely bound to IGF binding proteins (predominantly IGFBP-3 in the ternary complex with the acid-labile subunit). Quantifying total IGF-1 requires either a method robust to the binding-protein interference, or a sample-preparation step that releases IGF-1 from the binding proteins prior to measurement. The chemistry of how each assay handles this problem is the largest source of inter-platform divergence.

Antibody pair specificity: each commercial immunoassay uses a different monoclonal antibody pair, recognizing different epitopes on IGF-1; some epitopes are more accessible than others when the molecule is in its native binding-protein-bound form, and small differences in antibody specificity produce measurable systematic differences in reported values. IGFBP interference resistance: modern assays release IGF-1 from binding proteins (typically through acid-ethanol extraction or pH manipulation) and incorporate excess IGF-2 or anti-IGFBP reagents to block residual binding-protein interference; older platforms with less effective IGFBP-suppression chemistry can show lower apparent IGF-1 values because part of the bound fraction is not measured. Calibration material traceability: even when assays are nominally calibrated against the WHO IS 02/254 standard, the calibration is implemented through manufacturer-internal secondary standards, with batch-to-batch variation introducing slow drift over time. Matrix effects: serum versus plasma, the anticoagulant used (EDTA versus heparin versus citrate versus none), and freeze-thaw history all affect the apparent IGF-1 concentration on some platforms more than others. IGF-1 variant detection: native IGF-1 circulates as multiple post-translationally modified variants, and the DeGruyter Brill 2024 cohort examining over 240,000 patient samples documented systematic variant-detection differences across platforms with implications for binding-protein-bound IGF-1 measurement.

The cumulative effect is that the same serum sample, drawn at one venipuncture and split across the major platforms, produces values that can differ by 30-80% between the lowest-reading and highest-reading platform on the same specimen. This is documented across multiple published comparison studies and is not a controversial finding.

The cross-platform conversion problem

A natural question for a member with serial IGF-1 values across different platforms is whether a published conversion factor allows one set of numbers to be converted into another. The honest answer: there is no universally accepted, batch-stable, time-invariant conversion factor between any pair of commercial IGF-1 platforms.

The Bidlingmaier 2014 multicenter dataset and its derivatives form the closest thing the field has to a cross-platform reference. The dataset established age- and sex-adjusted reference intervals on the iSYS platform across 15,014 subjects from twelve cohorts in North America and Europe (Bidlingmaier et al. 2014). Other platforms have published their own age- and sex-stratified reference intervals; the Chanson 2016 VARIETE cohort comparison documented that even within the same 900-subject French population, the six platforms produced reference intervals with noticeably different upper limits (the 97.5th percentile values varied markedly across assays) while the lower limits (2.5th percentile values) were more similar.

The standardization-as-state-of-the-field summary published by the Huang et al. Crit Rev Clin Lab Sci 2024, 61:388-403 review documents what the modern harmonization effort has and has not achieved. The achievements: most major platforms now calibrate against the WHO 02/254 standard, IGFBP-suppression chemistry has converged across the leading platforms, and several efforts toward LC-MS/MS-based reference measurement procedures are underway. The persisting gaps: pairwise concordance between any two platforms remains in the moderate-to-good range (weighted kappa 0.38-0.70 in the Chanson 2016 comparison), the upper-reference-limit divergence is not fully addressed by WHO-standard calibration alone, and several manufacturers have continued to refine their assays year-on-year in ways that produce calibration drift even within the same nominal product line. The Dutch 2024 external quality assessment study referenced in the Huang review documented that IGF-1 results differed by a factor of 1.5 to 2 between immunoassays on the same external quality samples, and that LC-MS/MS results sat 0-60% lower than the immunoassay values.

The operational implication: a member who needs to compare values across platforms can use the Bidlingmaier 2014 SDS framework (standard-deviation-score adjustment relative to the iSYS-derived reference intervals) as a coarse approximation, with the understanding that the SDS calculation itself is platform-specific and the comparison across platforms produces an estimate, not an equivalence. The Chanson 2016 paper documented that while raw values differed significantly across assays, when expressed as standard-deviation scores against each assay's own reference data, the global interassay differences were not statistically significant. This is the best available cross-platform interpretation framework, and it remains an approximation.

Age stratification

IGF-1 declines with age in both sexes after the pubertal peak, with the trajectory continuous and steep enough that the age-of-the-patient matters more than any single absolute number. The Bidlingmaier 2014 multicenter dataset characterized the age trajectory across the lifespan: IGF-1 increases from birth through approximately age 15 (the pubertal peak), then declines continuously through adulthood and into senescence. The 2.5th-to-97.5th-percentile reference intervals at each age decade in the dataset (iSYS platform, sex-stratified) capture the population spread.

The general shape of the age-stratified ranges across the major commercial platforms, framed in approximate ng/mL terms (with the caveat that the absolute values shift across platforms by the magnitudes documented above), tracks the following pattern in adult life. Twenty-year-olds sit at the upper end of the adult distribution. Each decade of age decreases both the 2.5th-percentile lower bound and the 97.5th-percentile upper bound. By the seventh decade, the upper-limit-of-normal value on most platforms is in the same range as the lower-limit-of-normal value at age 25. The exact numbers vary by platform; the Bidlingmaier 2014 paper publishes the iSYS-platform-specific age-decade ranges, and members on other platforms should look up their lab's published age- and sex-stratified reference intervals rather than relying on cross-platform extrapolations.

This is why the "compared to normal" framing common in peptide-community discourse is not adequate. A 45-year-old user with an IGF-1 of 215 ng/mL sits at the population mean for their age decade on the iSYS platform; a 65-year-old with the same value sits above the population mean for their age decade. The "is the value high or low" question cannot be answered without the age-specific platform-specific context.

The "youthful target" framing — some practitioners aim for IGF-1 values comparable to a person twenty or thirty years younger than the user's chronological age — is a mechanistic hypothesis about restoring an age-related decline, not a validated clinical-outcome target. The hypothesis is plausible at the GH-axis pharmacology level; the evidence that restoring youthful IGF-1 values produces the corresponding youthful clinical phenotype is much thinner. The "youthful target" framing should be understood as a working framework rather than a documented therapeutic threshold.

The supranormal IGF-1 question

A separable methodological concern: IGF-1 above the age-adjusted upper limit of normal sits in a region the epidemiology and acromegaly literature treats with caution. The Renehan et al. Lancet 2004, 363:1346-1353 systematic review and meta-regression analysis documented an association between higher circulating IGF-1 concentrations and increased risk of prostate cancer (odds ratio 1.49 comparing 75th-to-25th percentile, 95% CI 1.14-1.95) and premenopausal breast cancer (1.65, 95% CI 1.26-2.08). The associations were modest and varied by cancer site; no significant associations were identified for colorectal, postmenopausal breast, or lung cancers in that analysis.

The mechanism-versus-cohort framing matters in interpreting this literature. The Renehan analysis was a meta-regression of observational case-control data, so the IGF-1 values were not pharmacologically manipulated; the IGF-1 elevation was a property of the individuals in the cohort, and the association may reflect shared upstream causes (insulin resistance, body composition, dietary factors) rather than a direct causal effect of IGF-1 on cancer risk. The translational question — whether pharmacologically elevating IGF-1 through GH-secretagogue therapy produces the same risk profile as endogenously high IGF-1 — is not directly answered by the Renehan data and remains an open empirical question with limited direct trial evidence.

The acromegaly literature offers the closest available human evidence on chronically supraphysiologic IGF-1. The most recent consensus on acromegaly therapeutic outcomes (15th Acromegaly Consensus Conference, Nat Rev Endocrinol 2025) anchors treatment targets at IGF-1 normalization (within the age-adjusted reference range) rather than at any specific absolute value, with the framing that chronic IGF-1 elevation above the age-adjusted upper limit is associated with the cardiovascular, metabolic, and oncologic comorbidities the acromegaly literature documents. The relevance of this framing to a biohacker pursuing supraphysiologic IGF-1 on a GH-secretagogue cycle is partial — the acromegaly population has decades of cumulative exposure to GH excess and additional pituitary-tumor pathology, not just a six-week IGF-1 elevation — but the directional concern is well-supported.

The Egrifta WR tesamorelin prescribing information operationalizes the supraphysiologic threshold by recommending regular IGF-1 monitoring with consideration for discontinuation in patients with persistent elevations above 3 SDS (standard-deviation score relative to the age-adjusted reference range). The 3-SDS threshold is one operational anchor; the Endocrine Society 2014 acromegaly guideline and subsequent consensus documents anchor treatment targets at age-adjusted within-normal-range IGF-1 rather than any specific cutoff. Members on chronic GH-secretagogue cycles whose IGF-1 sits persistently above the age-adjusted upper limit are in the region the published literature treats with monitoring caution.

What changes between platforms — and what does not

The platform-divergence problem is concentrated in three areas. Absolute values differ across platforms by 24% to 81% systematic bias on identical samples in the published comparison literature; serial IGF-1 values from different platforms cannot be directly compared in ng/mL terms without large interpretation error. Reference ranges differ at the upper end (the 97.5th-percentile upper limits diverge most across platforms per Chanson 2016) more than at the lower end (the 2.5th-percentile lower limits are more similar). Z-scores and SDS are computed against each platform's own reference dataset; an SDS of +1 on one platform is not biologically identical to an SDS of +1 on another, although the convergence is better than for raw values (Chanson 2016 documented that interassay differences in raw values were statistically significant while differences in SDS values were not).

What is more stable across platforms: the within-platform trajectory (a pre-cycle-to-mid-cycle delta measured at the same lab on the same platform reflects biological change modulo intra-individual variability on the order of 10-20%); the direction of change (a robust pharmacological effect produces an IGF-1 elevation on every platform, even though the absolute magnitude in ng/mL differs); and the qualitative interpretation against platform-specific reference (a value at the 90th percentile of a platform's age-adjusted distribution is broadly the same biological state across platforms even when the corresponding ng/mL number differs).

Practical implications for peptide cycle monitoring

The methodological frame translates into a small number of operational recommendations for a member tracking IGF-1 across cycles. These are informational rather than prescriptive; the cycle-decision layer belongs in discussion with a treating clinician.

Single-vendor, single-platform monitoring is the simplest workaround. A member who draws every IGF-1 across cycles at the same lab vendor, on the same platform, removes the cross-platform bias term from the data. The remaining variation is the actual biological variation (analytical CV plus intra-individual variability plus pharmacological effect). Multi-vendor monitoring introduces a platform-bias term that, in many cases, will dominate the pharmacological signal.

Document the platform alongside the value. Recording "IGF-1 = 220 ng/mL, IDS iSYS, LabCorp specialty test, drawn 2026-03-14" preserves the information needed to interpret the value across time. Recording "IGF-1 = 220" preserves enough information to mislead. Most major commercial laboratories will identify the IGF-1 platform on the report itself or in the test directory; LabCorp's 010540 test code uses the IDS iSYS platform with Z-score reporting, Quest's 16293 test code uses the LC-MS/MS method, and the platforms vary across other test offerings and across reference laboratories.

Compare to age-stratified ranges within the platform. The right comparison for any IGF-1 value is to the platform's own age- and sex-stratified reference interval, not to "adult normal" or to an internet-circulated target value. Most major commercial laboratories now publish age-decade reference intervals; the patient or member can look up the relevant decade from the lab's test directory or the report itself.

SDS or Z-score reporting is the most cross-platform-portable framework. Where the platform publishes an SDS or Z-score against its own reference dataset, the SDS value is the most-comparable cross-platform metric. An SDS of +1.5 on one platform is broadly the same biological state as an SDS of +1.5 on another, even when the underlying ng/mL values are non-comparable. This is the framework the acromegaly-management literature has converged on, and it is the framework the Egrifta WR label operationalizes for its IGF-1 monitoring guidance.

Account for intra-individual variability. Even on the same platform, a single individual's IGF-1 fluctuates 10-20% across short time intervals from analytical CV plus diurnal and inter-day biological variation. A delta smaller than 20% between two timepoints on the same platform is in the regime where intra-individual noise is competitive with the pharmacological signal; deltas of 30-50% or more cross out of the noise regime and into the regime where the pharmacological signal is unambiguous.

LC-MS/MS where available. Mass-spectrometry-based IGF-1 measurement is the gold-standard reference method and is broadly insensitive to the antibody-pair-specificity issues that drive immunoassay divergence. Quest Diagnostics offers an LC-MS/MS IGF-1 method (test 16293); ARUP and some academic reference laboratories also offer mass-spectrometry-based IGF-1. The LC-MS/MS methods are not perfectly equivalent to each other either — inter-laboratory LC-MS variation exists — but the magnitude of the variation is smaller than the immunoassay variation, and the mass-spectrometry results are typically used as the reference against which the immunoassays are evaluated.

The Mediagnost research literature anchor

A separate practical implication concerns comparing personal IGF-1 values to "literature" values reported in published peptide trials. Much of the academic IGF-1 literature, particularly the European GH-axis work, anchored on Mediagnost RIA / IRMA / ELISA platforms before the iSYS-based multicenter dataset became the contemporary reference. When a published trial reports a mean IGF-1 of 195 ng/mL at baseline in a GH-secretagogue cohort, the implicit platform is often Mediagnost-equivalent — which reads similarly to the iSYS platform but does not directly cross-convert to the IMMULITE, DiaSorin, or Roche platforms. The published Tesamorelin pivotal Phase III program and the Khorram et al. 1997 Sermorelin trial used assay platforms documented in the respective publications, but commercial lab platforms have shifted across the intervening two to three decades; direct comparison of a contemporary commercial IGF-1 value to the trial-reported baseline numbers is subject to the cross-platform conversion uncertainty described above. The published trials are more useful as references on the direction and magnitude of change than as references on the absolute baseline value a member should expect.

Worked example: tracking a GH-secretagogue cycle

A 45-year-old user begins an Ipamorelin plus CJC-1295-DAC protocol with structured biomarker monitoring. The methodologically sound version of the dataset draws all three timepoints — baseline (week 0), mid-cycle (week 6), and end-cycle (week 12) — at the same LabCorp draw center on the IDS iSYS platform via test code 010540, with Z-scores reported against the age-adjusted reference. A trajectory from 175 ng/mL (Z = -0.4) at baseline to 245 ng/mL (Z = +0.9) at mid-cycle to 265 ng/mL (Z = +1.3) at end-cycle shows a robust within-platform pharmacological elevation of 1.7 SDS. The absolute numbers and the SDS rise are both internally consistent; the end-cycle Z-score sits within the age-adjusted reference range and well below the Egrifta WR label's 3-SDS discontinuation threshold.

The methodologically problematic version: the same three draws, but at three different vendors, with the platform unspecified on each report. The trajectory shows an apparent rise from 175 to 245 to 220 ng/mL across the three timepoints. Whether the apparent rise to mid-cycle reflects pharmacology or reflects an IMMULITE-to-iSYS platform shift (which alone could account for 30-80% of the observed difference) cannot be determined from the data. Whether the apparent end-cycle decline reflects pharmacological reversion or a third platform shift depends on details the dataset does not capture. The pharmacological signal is not extractable from the platform-confound term.

The difference between the two versions is operational, not analytical. The same blood draws can produce either dataset; the choice of how to structure the measurement determines whether the resulting numbers are interpretable.

Cross-link to the platform's biomarker registry

The site's member-platform biomarker registry at /members/biomarkers captures IGF-1 measurements with optional lab vendor and platform metadata, structured specifically to preserve the platform-comparison information this dossier describes. The k≥5 anonymity floor described in the peptide research glossary defines the aggregation discipline: no community-level pattern is surfaced unless at least five independent members contribute to the bucket, and the aggregation respects platform-consistency boundaries (cross-platform pooling is flagged in the data layer rather than silently averaged).

The infrastructure premise: when many members structure their own monitoring with platform metadata, the aggregated cohort-level data preserves the cross-platform interpretation problem rather than averaging it away. A community-aggregated IGF-1 trajectory for Ipamorelin plus CJC-1295 protocols that is platform-stratified — separate aggregations for the iSYS-platform, IMMULITE-platform, Roche-platform, and DiaSorin-platform subsamples — is the data infrastructure that allows the field to move from "what's a normal IGF-1 on a cycle" anecdote to platform-specific community reference distributions.

What this reference is not

It is not medical advice. The decision of whether to draw IGF-1, which lab to use, and how to interpret out-of-range values belongs in discussion with a treating clinician.

It is not a substitute for the platform-specific reference intervals published by the laboratory performing the measurement. The age-decade ranges in this dossier are general framings; the operationally correct reference is the lab's own published age- and sex-stratified intervals for the assay in use.

It is not a recommendation to pursue any specific IGF-1 target. The site does not recommend therapeutic IGF-1 ranges, supraphysiologic targets, or pharmacological interventions. The framing on every section above is informational; the prescriptive layer belongs in a physician relationship.

It is not exhaustive on the published platform-comparison literature. The comparison studies cited above are anchors; the broader literature includes ~200 papers across the last two decades on IGF-1 standardization, platform comparison, mass-spectrometry reference development, and reference-interval establishment. This dossier covers the load-bearing references that anchor the practical conclusions; readers pursuing the topic deeper should follow the citations in the Huang 2024 review for the contemporary literature map.

Closing frame

The IGF-1 measurement problem is the methodological foundation underneath the entire GH-axis monitoring practice. A member who structures their own measurement to remove the platform-divergence confound produces interpretable serial data; a member who structures their measurement without attention to platform consistency produces data that mixes the pharmacological signal with the analytical drift in ways that are not separable after the fact. The difference is not subtle — the published platform-comparison literature documents the magnitudes, and the magnitudes are large enough to qualitatively change cycle decisions. The peptide community has not, historically, treated IGF-1 platform divergence with the seriousness the clinical-laboratory and acromegaly-management communities have. The harmonization efforts underway and the LC-MS/MS reference-method development may, over time, narrow the cross-platform divergence; the Huang 2024 review documents both the progress and the remaining gaps. The current version of this dossier is dated 2026-05-18.

Sources cited

External canonical references:

• Bidlingmaier et al., J Clin Endocrinol Metab 2014, 99:1712-1721 — Reference intervals for IGF-1 from birth to senescence, multicenter study, iSYS-platform calibration (15,014 subjects)
• Bidlingmaier et al., corrigendum, J Clin Endocrinol Metab 2020, 105:e4983 — SD score calculation correction to the 2014 reference-interval paper
• Chanson et al., J Clin Endocrinol Metab 2016, 101:3450-3458 — Reference values for IGF-1 serum concentrations: comparison of six immunoassays (VARIETE cohort, ~900 healthy French adults)
• Lee et al., Clin Chim Acta 2023, 539:1-7 — Discordance of IGF-1 results on four different platforms (IMMULITE 2000, LIAISON XL, iSYS, LC-MS/MS)
• Mohammed-Ali et al., Clin Biochem 2022, 108:14-19 — Bias in IGF-1 concentrations across three clinical assays (DiaSorin LIAISON XL, Roche Elecsys, LC-MS)
• Huang et al., Crit Rev Clin Lab Sci 2024, 61:388-403 — Challenges of insulin-like growth factor-1 testing (modern standardization landscape review)
• Burns et al., Growth Horm IGF Res 2009, 19:457-462 — First International Standard for IGF-1 (WHO IS 02/254) preparation and calibration
• Renehan et al., Lancet 2004, 363:1346-1353 — IGF-1, IGFBP-3, and cancer risk: systematic review and meta-regression
• Egrifta WR (tesamorelin) prescribing information, FDA 2025 — IGF-1 monitoring and 3-SDS discontinuation threshold
• 15th Acromegaly Consensus Conference, Nat Rev Endocrinol 2025 — Consensus on acromegaly therapeutic outcomes (IGF-1 normalization as target)
• Katznelson et al. Endocrine Society Acromegaly Guideline, J Clin Endocrinol Metab 2014, 99:3933-3951 — Acromegaly clinical practice guideline (IGF-1 target framing)
• DeGruyter Brill, Clin Chem Lab Med 2024 — Detection rate of IGF-1 variants in over 240,000 patients

In-corpus references:

• Biomarker monitoring guide for peptide users — practice-level GH-axis monitoring panel
• Peptide research glossary — k≥5 anonymity floor and Z-score / SDS terminology
• GH-axis dossier — pulsatile-versus-tonic GH signaling and IGF-1 dynamics
• GH-secretagogue discontinuation playbook — off-cycle IGF-1 trajectory and timing
• MK-677 long-cycle taper playbook — chronic dosing and IGF-1 plateau dynamics
• Sermorelin, Tesamorelin, CJC-1295, Ipamorelin, MK-677, Hexarelin, GHRP-2, Anamorelin, IGF-1 LR3 — peptide-class entries that depend on IGF-1 as the central target marker
• Khorram et al. 1997 — Sermorelin in older adults (historical assay-platform context)
• Falutz et al. 2010 — Tesamorelin pooled Phase III data
• Nass et al. 2008 — MK-677 in older adults (two-year IGF-1 trajectory data)