Thursday, May 28, 2026

UDLCO point of care dyadic to triadic triangulation and beyond: Pregnancy congenital anomalies for termination and hypokalemia

 Introduction : We begin with a structured analysis of a conversational learning transcript between two caregivers, breaking down the clinical case, the key medical concepts, and a deeper philosophical evaluation of the patient privacy dilemma.




1. Executive Summary


The transcript captures a clinical consultation between two healthcare providers (hu1 and hu2) managing a complex case involving a 35-year-old pregnant woman at 20 weeks and 2 days gestation. The patient presents with profound, asymptomatic hypokalemia (potassium levels of 2.2 and 2.6 mmol/L).


While addressing this acute electrolyte imbalance, a second-trimester targeted ultrasound (TIFFA scan) reveals severe, multi-system fetal anomalies, including Arnold-Chiari II malformationopen spinal dysraphism (myelomeningocele), and bilateral club feet. The dialogue shifts from immediate stabilization (intravenous KCl replacement) to investigating the underlying etiology of the maternal hypokalemia and preparing for a likely termination and subsequent fetal autopsy, expanding the conversation from a clinical dyad into a multi-departmental investigation.


2. Key Words

  • Hypokalemia: Critically low blood potassium levels (maternal level $\leq$ 2.6 mmol/L), carrying risks of cardiac arrhythmias.

  • Arnold-Chiari II Malformation: A congenital central nervous system anomaly characterized by downward displacement of the cerebellum and brainstem through the foramen magnum.

  • Open Spinal Dysraphism: A neural tube defect (e.g., myelomeningocele) where the spinal cord and meninges protrude through a vertebral defect.

  • Lemon Sign & Banana Sign: Classic ultrasound markers indicating fetal cranial collapse (frontal bones) and cerebellar molding associated with spina bifida.

  • Pre-analytical Factors: Variables occurring before laboratory analysis (e.g., delayed transport in high heat) that can cause artifactual or "spurious" lab results.

  • Fetal Autopsy: Post-mortem examination of the fetus to confirm ultrasound findings, uncover syndromic links, and guide future genetic counseling.


3. Thematic Analysis

Theme 1: The Diagnostic Parallel Track

The caregivers are forced to manage two distinct clinical crises concurrently:

  • The Maternal Track: Correcting a potentially life-threatening potassium deficit ($2.6 \text{ mmol/L}$) and parsing whether it is a pre-analytical artifact or a systemic maternal-fetal pathology.

  • The Fetal Track: Navigating a devastating prognosis of severe structural and neurological abnormalities that heavily point toward an unviable pregnancy or profound lifelong disability.


Theme 2: Evolution of Caregiver Networks

The communication structure evolves dynamically. It begins as a localized, informal, digital chat between an OB-GYN/resident (hu1) and a consultant (hu2). However, as the medical complexity deepens—linking maternal endocrinology/nephrology with fetal pathology—the data network expands. The involvement of pathology services for a potential autopsy transitions the care model from a private dyad to an institutional triad and beyond.


4. Socratic Steelman: Privacy vs. The Transparency Quest

The expansion of this case network directly triggers a profound ethical friction point: Where does a patient's absolute right to the privacy of their medical narrative end, and where does the scientific community's duty to transparency for the greater good begin?


To explore this, we examine the strongest possible arguments (steelmen) for both sides of the debate.


Perspective A: The Steelman for Patient Privacy & Autonomy

Core Premise: The patient’s data is an extension of their bodily and psychological self. Unauthorized or overly broad dissemination—even anonymized—is a violation of trust, particularly during periods of intense vulnerability.


  • The Vulnerability Argument: This patient is dealing with an elderly pregnancy (35 years old), a dangerous medical condition, and the heartbreaking realization that her unborn child has catastrophic defects. Forcing her data into wider academic or cross-departmental networks without explicit, granular consent strips her of agency when she has little left.


  • The Chilling Effect: If patients realize that rare, fascinating, or complex combinations of their medical anomalies (like maternal hypokalemia paired with Chiari II malformation) are treated as open-source scientific puzzles by clinicians on digital chat networks, they may withhold history, skip diagnostic tests, or avoid care out of fear of being exposed or studied.


  • The Anonymization Myth: In highly specific cases (35F, 20 weeks pregnant, specific geographic location/date, exact kidney measurements, rare fetal anomalies), true anonymization is incredibly difficult to maintain. Re-identification risks remain high within local health systems, violating the foundational principle of primum non-nocere (first, do no harm).


Perspective B: The Steelman for Scientific Transparency & Collective Good

Core Premise: Medical progress relies entirely on the aggregation and analysis of real-world patient events. Restricting data sharing to strict, bureaucratic siloes halts scientific discovery and costs future lives.


  • The Epidemiological Duty: The association between severe maternal hypokalemia and major neural tube defects could be purely coincidental, or it could be a clue to an undiscovered genetic syndrome, metabolic pathway, or environmental toxicity. If clinicians do not transparently share this data across departments (Pathology, Nephrology, Genetics), a vital piece of the broader public health puzzle remains hidden.


  • The Accountability & Peer Review Argument: Broad data sharing ensures clinical safety. When hu2 brings in pathology and references open-access literature, it subjects the case to systemic checks and balances. Transparency protects the patient from localized clinical blindspots and ensures the medical decisions made are robust, accurate, and evidence-based.


  • The Reciprocal Social Contract: The patient benefits from medical knowledge built on the shared data of thousands of anonymous pregnant women who came before her. Therefore, a reasonable, non-identifiable trade-off exists: sharing her clinical timeline contributes to the collective pool of knowledge, giving meaning to a tragic clinical outcome by protecting future families.


The Socratic Synthesis: Is it a Reasonably Acceptable Trade-off?

The tension resolves not by choosing one side, but by asking a fundamental question: Can transparency be achieved without weaponizing the patient's data against their privacy?


The trade-off becomes reasonably acceptable only when clinical data sharing transitions from an ad-hoc, informal channel into a structured, permissioned protocol. As hu2 wisely notes in the transcript:


"Would become easier if we take her consent and structure our queries accordingly"


This acknowledgment bridges the gap. Transparency does not require total exposure, and privacy does not require total isolation. By implementing immediate, dynamic consent protocols, healthcare systems can honor the sacred, private bubble of the caregiving dyad while still allowing the de-identified clinical pearls of the case to feed the scientific quest for global medical progress.



Provide a summary, key words and thematic analysis of the content with an additional Socratic steelman focus on the tussle between patient privacy in patient events data sharing and the scientific quest toward transparency and accountability for the greater good where patient events data sharing may or may not appear as a reasonably acceptable trade off. 


Conversational learning dyadic Transcripts between two caregivers around a single patient:

[28/05, 10:17]hu1: there is refferal from obgyn around a 35F pregnant woman at 20 weeks.

In view of potassium 2.6 

Pt is asymptomatic no complaints of muscle weakness fatigue and she's on thyroxine 37.5 mcg since 8 weeks.


[28/05, 10:18] hu1: ECG of that pt sir

[28/05, 11:10]hu2: Thanks

Ask them to repeat the K+ asap and start 
40 mmol (= two 10 ml ampoules of 15% KCl) in  normal saline over 4 hours. Do not exceed 10 mmol/hour.

[28/05, 11:11] hu1: Ok her potassium is 2.6 sir now


Asymptomatic 


[28/05, 11:11]hu2: Why do they think the child has congenital anomalies? Share the report of anomaly scan


[28/05, 11:14] hu1: Yesterday it was 2.2 sir we repeated today mrng it’s 2.6 
Was adviced potklor 10ml tid 
She is not having any symptoms


[28/05, 11:15]hu2: Alright.

Let's try to find out why she could be having hypokalemia.

Would become easier if we take her consent and structure our queries accordingly


[28/05, 11:15]hu1: Report of her ultrasound copied below:

Placenta is posterior, upper and mid uterine segment and of Grade - " I " maturity.  

Amniotic Fluid: Is adequate (Single deepest vertical pocket measures 4.5 cms)  

Approx foetal weight : 331 +/- 48 gms.  
Umbilical cord vessels : 2 arteries and one vein.  

E.D.D : 10 / 10 / 2026 (According to Ultrasound measurements).  

*Screening of bilateral maternal kidneys appear normal.*  

*Right kidney : 104 x 41 mm ; Left kidney : 114 x 41 mm*  
*No e/o calculi / hydronephrosis.*  

*IMPRESSION :*  

*SINGLE LIVE INTRA UTERINE FOETUS WITH VARIABLE PRESENTATION.*  
*G.A. 20 WEEKS 2 DAYS.*  

*ADEQUATE LIQUOR.*  

*SCALLOPING OF BILATERAL FRONTAL BONES WITH LEMON SIGN.*  
*CROWDING OF POSTERIOR FOSSA WITH CURVED CEREBELLUM AND REDUCED TRANSCEREBELLAR SHOWING BANANA SHAPED CONFIGURATION WITH EFFACEMENT OF CISTERNA MAGNA.*  

*HYDROCEPHALUS WITH DEFECT IN ANTERIOR FALX AND NON VISUALIZATION OF CAVUM SEPTUM PELLUCIDUM*  

*- S/O AGENESIS OF CORPUS CALLOSUM.*  

*KYPHOSCOLIOTIC DEFORMITY AT LUMBOSACRAL REGION WITH SPLAYING OF POSTERIOR ELEMENTS AND WELL DEFINED ANECHOIC POSTERIOR CYSTIC SPINAL LESION COMMUNICATING WITH SPINAL CANAL WITH THIN INTERNAL SEPTATIONS - S/O OPEN SPINAL DYSRAPHISM WITH MENINGOCELE / MYELOMENINGOCELE.*  

*PERSISTENT MEDIAL DEVIATION OF BILATERAL FEET WITH ABNORMAL ALIGNMENT IN RELATION TO TIBIA AND FIBULA*  
*- S/O BILATERAL CLUB FEET.*  

*- FEATURES IN FAVOUR OF ARNOLD CHIARI II MALFORMATION.*

---
This report describes multiple fetal anomalies seen on ultrasound at 20 weeks 2 days. 


[28/05, 11:21]hu2: Currently she has a single 12 year old child?

[28/05, 11:25]hu1: Yes 

[28/05, 13:16]hu2: Spurious hypokalaemia can occur due to pre-analytical factors such as delayed transport of blood samples which are exposed to high ambient temperatures, which stimulates cellular potassium uptake

But more importantly if this is true hypokalemia one needs to understand as to why she developed this hypokalemia in her pregnancy

Here's a starter 👇


Hu2 subsequently informs pathology services for a potential fetal autopsy after fetal removal taking the current dyadic conversation to triadic and beyond especially when the case is discussed between multiple departments in the context of Socratic questions raised around the probable associations between the patient's elderly pregnancy, fetal anomaly detection on ultrasound surveillance aka
TIFFA scan, which is Targeted Imaging for Fetal Anomalies (often done during the second trimester, between the 18th and 22nd week of pregnancy) and the unexpected hypokalemia. 

Wednesday, May 27, 2026

UDLCO CRH: The core issue in modern medicine is that guidelines based medicine GBM is heavily adopted, while true EBM is often underutilized

 The core issue in modern medicine is the divergence between Guidelines-Based Medicine (GBM), which relies on standardized, population-level protocols, and Evidence-Based Medicine (EBM), which integrates best research, clinical expertise, and individual patient values. GBM is heavily adopted, while true EBM is often underutilized. [1, 2, 3, 4, 5]





The Disconnect: GBM vs. EBM
Concept [1235678]Definition & ImplementationThe Real-World Issue
Guidelines-Based Medicine (GBM)Adherence to standardized, institutional, or national treatment protocols and pathways. Often mistaken for true EBM.Over-reliance creates a "cookbook" approach. It enforces population-level norms for individual patients who may not fit the exact statistical profile.
Evidence-Based Medicine (EBM)The integration of current scientific evidence, clinical expertise, and the specific values and preferences of the patient.True EBM requires immense time, resources, and critical evaluation of conflicting or slow-to-update clinical trials. It is harder to scale than rigid guidelines.

Why This Imbalance Exists
  1. Time and Workflow Constraints: In busy clinical practices, it is highly efficient to default to predetermined, algorithmic guidelines rather than conducting an individualized EBM literature search for every patient.
  2. Standardization and Litigation: Hospitals utilize GBM to maintain quality control, ensure baseline standards of care, and protect against medical-legal issues.
  3. The Complexity of the EBM Triad: True EBM fails when doctors focus exclusively on the clinical evidence and minimize the other two core pillars: clinical expertise and patient values. [591011]
The Impact on Complex Care

This imbalance is particularly visible in highly complex, heterogeneous diseases (such as Glioblastoma in oncology).
  • Guidelines dictate broad, population-level standards (e.g., maximal safe surgical resection followed by radiation and temozolomide).
  • However, because every tumor is biologically different and every patient has unique goals and tolerances, clinicians must rely on EBM to tailor treatments based on specific molecular/genetic markers and the patient's individual quality-of-life preferences. [113141516]
Resources for understanding how clinical guidelines are developed and the principles of EBM include:
  • The [MSD Manuals Evidence-Based Medicine and Clinical Guidelines](https://www.msd manuals.com) breakdown.
  • The StatPearls Evidence-Based Medicine Framework for a deep dive into the criteria and biases of EBM.

AI responses may include mistakes.

Monday, May 25, 2026

UDLCO CRH: Pharma driven vs academia driven global clinical trial integrity adjustment disorder

Summary of the Discussion after sharing the minutes of the journal club initially archived here: https://medicinedepartment.blogspot.com/2026/05/udlco-crh-sunday-journal-club-on.html?m=1





The transcript captures a debate between two clinicians (hu2 and hu7) regarding a recent journal club review of a metabolic dysfunction-associated steatohepatitis (MASH/NASH) commercial drug trial (specifically referencing Resmetirom data).


  • hu2 initiates the discussion by highlighting vulnerabilities in the trial design that could artificially inflate the drug’s apparent efficacy. They point to high placebo response rates, the breaking of double-blinding due to distinct drug side effects (diarrhea), and potential hidden manipulations within "grey literature" and protocols (such as post-hoc endpoint shifting and selective subgrouping) driven by massive commercial stakes.

  • hu7 counters these points by explaining the clinical and regulatory realities of modern trials. They argue that high placebo rates in MASH trials stem from the inherent subjectivity of liver biopsy histology (hepatocyte ballooning) rather than protocol manipulation. Furthermore, hu7 strongly defends the integrity of modern regulatory environments, noting that Statistical Analysis Plans (SAPs) must be locked before database unblinding, rendering intentional post-hoc inflation for primary approval impossible. They conclude that while bias exists, it is heavily regulated in pharma, whereas academic/NIH studies often suffer from worse post-hoc ("freezer study") biases.


## Keywords


  • MASH/NASH Resolution

  • Effect Size Inflation

  • Placebo Response

  • Double-Blinding Breakdown

  • Statistical Analysis Plan (SAP)

  • Post-Hoc Analysis

  • Grey Literature

  • Surrogate Endpoints

  • Regulatory Oversight (FDA/EMA)

  • Histologic Inter-observer Variability


## Thematic Analysis: Protocol Adjustments and Effect Size Inflation

The core of the debate centers on whether the trial's reported treatment effect was artificially amplified by structural protocol adjustments or design flaws. The arguments for both sides are categorized below:

1. Arguments FOR Protocol Adjustments & Factors Inflating Effect Size

This perspective, heavily championed by hu2, focuses on how commercial trial design can be subtly optimized or exploited to maximize apparent drug benefits.

  • Breakdown of True Double-Blinding: Resmetirom’s physical signature—specifically a significantly higher rate of early-onset diarrhea (~34% vs. 16% in placebo)—acts as an unblinding mechanism. If patients and site coordinators guess the assignment, it introduces behavioral and reporting biases that inflate the drug's perceived efficacy.

  • Asymmetric Site-Level Reforcements: While hu7 notes this is a site bias rather than a "protocol change," unblinded coordinators might more aggressively encourage diet and lifestyle compliance in the active arm, falsely magnifying the marginal drug effect.

  • Subjectivity in Central Pathology Reading: Relying on central readers for qualitative microscopic endpoints (like hepatocyte ballooning, which must drop to 0 for "NASH resolution") creates a single point of failure. Borderline slides may be subtly upgraded toward "resolution" to satisfy commercial objectives.

  • Theoretical Grey Literature Manipulations: In a broader sense, industry sponsors can inflate efficacy by shifting primary endpoints post-hoc, utilizing suboptimal or low-dose comparators rather than head-to-head active controls, or shortening washout periods to handicap competing drugs.

  • Surrogate Endpoint Reliance: Achieving "NASH Resolution" at 52 weeks is an abstract, tissue-level metric that allows for accelerated regulatory approval but may overstate the actual, long-term clinical utility before 54-month hard outcomes (cirrhosis/survival) are proven.

2. Arguments AGAINST Protocol Adjustments & Effect Size Inflation

This perspective, presented by hu7, argues that structural guardrails and the nature of the disease pathology account for these data anomalies, rather than protocol manipulation.

  • Histological Imprecision, Not Manipulation: The high and variable placebo arm response is an artifact of the inherent difficulty in assessing liver biopsies. Because "ballooning" scores are highly subjective, minor variations among the panel of central readers naturally cause shifts in data, which is a known limitation of MASH histology rather than a deceptive protocol tweak.

  • Strict Regulatory Saps (Statistical Analysis Plans): Modern regulatory frameworks (FDA/EMA) strictly forbid post-hoc endpoint shifting for drug registration. The primary endpoints and statistical handling methods must be finalized and locked before the trial database is unblinded.

  • Nominal Value of Post-Hoc Data: Any post-hoc adjustments or subgroup analyses cannot legally be used to gain a primary drug indication. They are heavily policed, must be explicitly labeled as "post-hoc," and their p-values are relegated to "nominal" status, rendering them purely hypothesis-generating.

  • Academic Multi-Author Accountability: Registrational trials feature numerous non-industry academic authors (often as first and last authors) who must personally attest to the validity of the data, minimizing the likelihood of corporate data fabrication.

  • The "Academic Bias" Counter-Argument: The risk of true unscientific post-hoc manipulation and "freezer study" bias is statistically much higher in under-regulated, academic, and NIH-sponsored research than it is in highly audited, multi-billion-dollar pharmaceutical registrar trials.


Conclusion of the Analysis: The dialogue highlights a critical friction point in Evidence-Based Medicine. While trial designs suffer from practical limitations that can inflate effect sizes (such as blinding breakdown via side effects and subjective surrogate endpoints), modern regulatory mandates largely prevent the outright, clandestine protocol manipulation of primary endpoints in phase 3 commercial trials.


Provide a summary, keywords and thematic analysis of the discussion content below around the web linked journal club focusing on the points for and against how protocol adjustments may or may not have led to effect size inflation.

Conversational transcripts:

[24/05, 16:28]hu2: Questions after the Sunday journal club today:

1) The fact that 31 placebo patients resolved their NASH and 46 improved their fibrosis score without receiving an active molecule proves that the natural course of MASH is highly variable. In commercial trials with high financial stakes, the "placebo arm" isn't a passive vacuum; it is highly dynamic?

2) True double-blinding assumes that neither the patient nor the doctor can guess their treatment allocation. However, Resmetirom caused significantly higher rates of gastrointestinal side effects (diarrhea in ~34% of the 100-mg group vs. 16% in the placebo group).

Critical Caveat: When a drug has a distinct physical signature (like early-onset diarrhea), the "blind" often breaks down in practice?


3) When funding originates entirely from a commercial entity with billions of dollars on the line, subtle, unshared protocols within the "grey literature" can be adjusted to artificially maximize the drug's apparent benefit?

4)The trial highlights a classic Evidence-Based Medicine (EBM) paradox?. 

"NASH Resolution" is a microscopic, pathological endpoint. It is an abstract, non-patient-related metric accepted by regulatory bodies for accelerated approval.

While observational data suggests these tissue-level changes eventually track with survival, the 52-week data does not guarantee that a patient feels better or will avoid cirrhosis. 

The true trial runs for 54 months to observe hard clinical outcomes. However, multinational and generic corporations (like Torrent) are already leveraging the initial 52-week surrogate hype to establish market dominance and secure physician loyalty years before

A picture worth the thousand words from this journal club can be seen here:


[24/05, 19:32]hu7: Some thoughts, but first, a disclaimer. I’m not a gastroenterologist. That said, my thoughts on your points:

1) the high rate of placebo response may be due to the imprecision in histology reads. MASH resolution (w/o worsening of fibrosis) has the highest placebo response because there is a huge amount of variability in the assessment of ballooning - of the three histologic features of MASH, steatosis, ballooning, and lobular inflammation, ballooning has to be 0 for resolution. Most MASH studies use a panel of 3 central readers, and use scores for each component that are unanimous (all 3 give the same score), majority (2 give the same score), median or consensus if all 3 scores vary. This reduces the placebo response, but still the inherent imprecision becomes apparent when you observe the huge differences in placebo response between studies. And yes, pre-cirrhotic MASH can regress. The idea of a placebo subtracted difference (treatment effect) helps define the drug effect over and above a chance effect. 

2) you are correct about true double-blinding, but it’s most likely to happen in studies with drugs that cause massive weight loss. GI symptoms can be reported by participants on placebo too - we did a study for BAYER eons ago called EDIP with acarbose, and almost all participants complained of abdominal symptoms. 

3) protocols for completed studies are required to be shared on the clinicaltrials.gov website, and as supplements to manuscripts published in the NEJM and Lancet and possibly other journals too. 

Question for you: can you provide an example of how a protocol can be adjusted to augment a drug’s benefit, artificially or otherwise? 

4) your point is at the crux of approvals for MASH therapies: showing histologic efficacy will only get “accelerated approval” or provisional approval from the FDA and EMA. Full approval requires clinical outcomes - a drug that has accelerated/provisional approval will be withdrawn from the market if the clinical outcomes study doesn’t show benefit.  There is sufficient data to show that fibrosis improvement (w/o worsening of steatohepatitis) tracks with clinical outcomes, mainly progression from pre-cirrhotic to cirrhotic MASH - this is not the case for MASH resolution. 
Finally, while histology is not a patient-related metric, there are data to support the idea that histologic changes correcte with changes in patient-related outcomes such as NASH CHECK. But I think if a study had to be powered to show differences in PROs, it would be impossibly large.


[24/05, 20:21]hu2: Excellent points 👏

Your point 3 question has been answered in the article with two examples, one pertaining to the standard of care life style interventions and the other that you have actually addressed in point 1. I quote,

"Tweakable Background Variables in Low-Integrity Environments


When funding originates entirely from a commercial entity with billions of dollars on the line, subtle, unshared protocols within the "grey literature" can be adjusted to artificially maximize the drug's apparent benefit:

Asymmetric Lifestyle Reinforcement: If trial site coordinators informally remind active-arm patients more aggressively about diet compliance (or if those unblinded by side effects self-select into healthier habits), the marginal drug effect is falsely magnified.


Central Pathologist Subjectivity: Relying on a single central reader for qualitative biopsy features (like hepatocyte "ballooning") introduces a single point of failure where borderline slides could be subtly pushed toward "resolution" to meet stringent corporate endpoints."

Unquote


[24/05, 20:27]hu7: Asymmetric lifestyle reinforcement by a coordinator is _*not_* a protocol adjustment. It’s a bias that’s introduced at the site level. It’s like the bias in reporting an AE, calling it drug-related or not, etc.



[24/05, 21:05]hu2: Also sharing a few more examples in general and unrelated to the current study 👇

When pharmaceutical sponsors hold massive financial stakes, unpublished, "grey literature" (like internal protocols and regulatory dossiers) can be manipulated to create an illusion of greater drug efficacy. This introduces significant bias into overall study outcomes. Common examples of these subtle, protocol adjustments include:


Shifting the Primary Endpoint Post-Hoc: Researchers may track dozens of health outcomes during a trial. If the drug fails to show significance on its original, pre-registered primary endpoint, sponsors might "adjust" internal protocols to promote a secondary, positive outcome—making the drug look like a success in marketing while burying the initial failure.


Selective Subgroup Analysis: A drug might perform poorly across the general trial population. To artificially boost its profile, internal protocols can be adjusted to hyper-focus on a small, specific subgroup (e.g., "patients over 60 without prior liver issues") where the drug happened to show a weak benefit.


Using Less-Than-Optimal Comparators: Instead of running "head-to-head" trials against the best existing medications, sponsors' protocols may mandate comparing the new drug to an inactive placebo or a suboptimal, low dose of an older drug, ensuring the new drug's results look significantly better.

Manipulating Washout Periods: In trials testing a drug against an old one, researchers can alter the protocol by shortening the "washout period" (the time allowed for patients to clear previous medications from their systems). This can skew baseline health conditions or increase adverse effects for the competitor drug, artificially making the new drug appear safer and more effective.

Redefining Normal Ranges: Protocols can adjust the definitions of what constitutes a "successful" response or a "mild" adverse event. Broadening the tolerance for what qualifies as a normal lab result can deliberately filter out negative side effects or inflate the percentage of patients categorized as "responsive" to the treatment.These behind-the-scenes manipulations often result in major Publication Bias, as unfavorable data is filtered out from public or peer-reviewed journals. 

For a comprehensive look at how these practices impact medical literature and prescribing guidelines, review the Qualitative Systematic Review on Financing of Drug Trials.Pharmaceutical industry sponsorship and research ... - PMC

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[24/05, 22:36]hu7: What is the source of this information? I suspect there’s some hallucination. 

Statistical analysis plans for registrational studies have to finalized and approved well before the study is complete (last participant last visit) and database is locked - usually, the  choice of an endpoint (and the primary statistical analysis method) that is registrable is discussed with regulators and finalized before the start of phase 3. 

_*Post-hoc_* analyses are considered purely hypotheses generating, and typically not used for a registered endpoint with an indication, and when these post hoc analyses are published, they are required to be marked as post hoc, and the p-values have to identified as “nominal”.  

There are instances of an Agency requiring a different type of analysis for the endpoint - even then the endpoint doesn’t change, just the analysis method. I’ve seen this happen with handling of missing data. 

Post hoc analyses can’t be used for an indication. Post-hoc analyses used for promotion requires them to be disclosed as post- hoc. 

Today’s regulatory environment is very different from what was prevalent say 20-25 years ago.

And another point, all publications of primary and key secondary data from clinical trials conducted by pharma have numerous authors from academia (typically they are first and last authors). They do attest that the results are correct, and they agree with the presentation. 

OTOH

I can point to many “adjustments” to studies sponsored by the NIH. Many papers from academia, especially ones called “freezer studies”, are so incredibly post-hoc, but rarely called out as such; but no one says the conclusions should not apply to clinical care, or describe disease pathology, or define biomarkers. 

And if you look at retracted publications, publications with fabricated references, spurious publications, etc., an overwhelming majority of them are from academia. 

So, at the end, there’s enough blame to go around, making it very hard for practicing clinicians: they need to learn to look at the data very dispassionately, understand the difference between pre-specified and post-hoc analyses, understand statistical analysis methods, handling of missing data, multiplicity control, etc., before making conclusions that affect patient care.


[25/05, 06:47]hu2: Agree!

Plenty of learning points here. 🙂🙏