Detailed Outline of Prevalence Strategy and Tricks

See slide here; full analysis click here.   The real “methodology” behind the higher prevalence claim is a linguistic conflation of distinct diseases into the single term, “FH.”

  • Before Big Pharma’s publication strategy, those with APOB mutations were defined as FDB. Those with PCSK9 were FH3. Those with LDLR were FH.
  • Regeneron’s “new” increase in prevalence requires a linguistic re-definition — a conflation of FDB and FH3 with “FH.” No screening in the field is required to increase prevalence. No new people are found.
  • Using linguistic conflation on established prevalence rates for the separate diseases, mathematics alone arrives at a higher prevalence. This means that the conflated prevalence claimed in the Regeneron-funded report is not higher than previously thought, but actually lower.

See Slide here; full analysis click here.   Geno-mandering: Big Pharma takes a page from political gerrymandering.  This is not science, but information strategy.

  • The previous Big Pharma authoritative reports focused on Denmark and The Netherlands. The choice was not accidental.
  1. White Europeans: Along with other nations with Central and Northern European ancestry, Denmark has an unusually high APOB mutation prevalence.  APOB is relatively rare elsewhere in the world.
  2. Founder Effect is a genetic anomaly which results in a higher than usual prevalence of genetic mutations. The influence of founder effect on Danish FH is “intermediate.” U.S. FH is not represented by the Danish.
  3. Founder Effect: Another study with financial ties focused on The Netherlands, already documented to be influenced by founder effect.
  • Now the Regeneron study moves us from white Europeans to white US residents of European descent.
  1. White Europeans: The Regeneron-funded study was of 98.4% whites, who were said to be of European descent.
  2. Founder Effect: The study included Lancaster, PA, which includes the Amish. Experts know that their founder effect results in the highest APOB prevalence in the world.

Slide here; full analysis click here. The reports add in groups that inflate results.

  • The 1st Danish report lowered the standard of clinical diagnosis without compensating for false positives. It also used “6” on-text as the clinical cutoff point, while using 5 off-text in the actual calculation, inflating the results even further.
  • The new Regeneron report discloses that it included a group which was inflated due to selection bias. It did not disclose however the LDLR and APOB breakdown of this inflated group or the breakdown in the population that did not include this group (the less selected population). Most likely a disclosure of this breakdown would emphasize the preponderance of APOB over LDLR in the less selected group, which would put a brighter light on the already present reversal of the established predominance of LDLR prevalence over APOB.  Most likely the breakdown would reveal a much lower number of LDLR in the unselected group, lowering prevalence for FH-as-LDLR even further.

See slide here; full analysis click here. Mathematical Leverage: Denominators of key fractions were inflated before calculating the results for LDLR (FH) and APOB (FDB) prevalence. For example, in the upper row of the table below, see the calculation of APOB prevalence, which was supposed to be distinct from LDLR — yet it was calculated with LDLR in the denominator (probands found/total probands: 19/142 = .1338). In the next row down, see APOB without LDLR added in.

Inflating key denominator to increase FH prevalence

The inflation of the denominator is also used in the calculation of LDLR prevalence.

See slide here; full analysis click here. The move from a genetic-based message to clinical scoring systems in practice swaps patient populations. In 3 steps, these academic molecular reports (1) provoke a sense of urgency with the genetic-based “underdiagnosis,” (2) mildly offer disclaimers of clinical “limitations,” (3) while presenting clinical scoring systems as standard practice. It works because most who pass clinical criteria are not carriers, and on the other hand, most who are genuine carriers do not pass clinical criteria. “Genetic testing […] is uncommon,” and so ironically, the prevailing clinical diagnostic procedure, regarded as sufficient, contributes to the underdiagnosis.  The academic use of genetic testing is only a message of urgency which passes the baton to the realm of action: the applied clinical scoring system, a selection bias in vivo.  As this baton changes hands, the genuine mutation carriers are swapped out and the false positives, swapped in.

Pages here & here: Reconciling the two Danish reports: Deduction exposes a shell game with 2 different constituents:

Reconciling both Danish reports on FH prevalence

See analysis here: “Citation Kiting.” There was no external, contemporary source in the industry’s authoritative report for the new prevalence and the criteria used. This “citation kiting” enables a “conclusion drift.” 1:137 prevalence becomes 1:200 from one report to the other, without a detailed contemporary explanation. A study of FDB-rich “whites of Danish descent” becomes a study of the “general population.” And “FH” as LDLR and “FDB” as APOB become “FH” as both LDLR and APOB.