====== 🧠 Observational Artifact ======

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An observational artifact is a pattern or association that appears in data but is **not truly reflective of a biological or causal relationship** — rather, it results from **biases, confounders, or methodological limitations** inherent in observational studies.
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===== 🔍 Definition =====
**Observational artifact** refers to an **illusory finding** or **misleading pattern** that emerges in **non-randomized data** due to:
  * Sampling bias
  * Selection effects
  * Incomplete control of confounders
  * Temporal or institutional variations
  * Unmeasured variables

===== 🧪 Example =====
> A retrospective study finds that patients receiving 30 Gy in 3 fractions had lower local failure rates.  
> However, the treatment choice was not randomized — it may reflect physician preference, patient performance status, or tumor burden.  
> ➤ The “effect” may be an **observational artifact**, not a true causal relationship.

===== ⚠️ Why It Matters =====
* Observational artifacts can be **mistaken for real effects**
* They often **influence clinical guidelines prematurely**
* Without proper statistical control, they **bias interpretation**

===== 🧱 Common Sources =====
  * Lack of randomization
  * Heterogeneous treatment practices over time
  * Learning curves in institutions
  * Retrospective data quality
  * Publication bias favoring “significant” findings

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Observational artifacts often masquerade as breakthroughs. Critical appraisal requires recognizing their methodological origin — not mistaking them for clinical truth.
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