Why Is There No Certainty in Cancer Treatment?

The Truth Within Uncertainty: Why Are There No “Definite” Answers on the Cancer Journey?

 Genetic and Epigenetic Heterogeneity: “Chaos Within the Tumor”

Cancer is not a homogeneous mass consisting of a single cell type. Intratumoral Heterogeneity is the name given to a situation in which even cells within the same tumor may have different genetic characteristics.

• Spatial Variation: Cells on the right side of a tumor may be sensitive to a drug, while those on the left may be resistant.
• Temporal Variation: While the dominant cell population dies when treatment begins, cells in the minority that are resistant to the drug may multiply over time and change the course of the disease.

This biological diversity is the most fundamental barrier to predicting a “definite outcome.”

 Individual Biology and the “Microenvironment” Effect

Not only the tumor, but also the “soil” in which it lives—the human body—is variable. Cancer cell behavior is closely tied to the patient’s Tumor Microenvironment.

• Immune Response: Even if two patients’ tumors are genetically identical, one patient’s immune system may recognize the tumor better while the other’s may be suppressed.
• Metabolism and Age: Liver function and coexisting conditions such as diabetes or hypertension directly affect how quickly chemotherapy drugs are broken down in the body and how effective they are.

 Statistical Probabilities vs. Individual Fate

Oncology literature speaks in statistical concepts such as “Median Survival” and “P-value” . But statistics apply to large groups, not to a single individual.

When a doctor says “70% success,” it means: “This treatment was successful in 70 of 100 people with characteristics similar to yours.” However, no biological method has yet been discovered to know in advance whether a patient belongs to that group of 70 or the remaining group of 30.

“Statistics are medicine’s compass, but every patient navigates their own sea alone.”

 Biological Evolution and Treatment Resistance

Cancer cells are dynamic structures programmed to survive. Just as bacteria develop resistance to antibiotics, cancer cells evolve under treatment-related Selection Pressure .

 The Limits of Imaging Technologies

Advanced methods such as PET-CT, MRI and CT are excellent tools, but they too have a “resolution limit.” Clusters of cells smaller than 3-5 millimeters may generally be invisible on these devices. “Clear imaging” means “no tumor of detectable size,” rather than “no cancer cells in the body.” This small distinction is the technical barrier to speaking with certainty.

 Balancing Clinical Benefit and Quality of Life

Success in cancer is more than “tumor shrinkage.” Sometimes a treatment shrinks the tumor while worsening the patient’s general condition; at other times, the tumor remains the same size (stable disease) while the patient enjoys good quality of life for years. Variation in these parameters from person to person makes it difficult to establish a “standard definition of recovery.”

 Managing Uncertainty: The Ethics of Honesty

In modern medicine, a physician’s role is to provide “realistic guidance” rather than false hope. False certainty:

1. Causes patients to make misguided plans for the future.
2. Undermines physician–patient trust by creating disappointment.
3. Increases the patient’s psychological devastation if recurrence occurs.

Conclusion and Assessment

Uncertainty in cancer treatment arises from the complexity of life , rather than the inadequacy of science. There is no certainty because every person is unique, every tumor is distinct and every treatment process is a living story.

But uncertainty does not mean helplessness. Where there is uncertainty, there is close monitoring, personalized strategies and constantly updated treatment plans. Moving forward with determined steps rather than definite promises is the safest path in oncology.

References 

• Hanahan D, Weinberg RA. (2011). Hallmarks of Cancer: The Next Generation. Cell. (Foundational work on the biological complexity of cancer).
• Fisher B. (1980). Laboratory and clinical research in surgery. Cancer Research. (Biological determinism vs. probabilities).
• National Comprehensive Cancer Network (NCCN) Guidelines. (2025). Patient and Professional Perspectives on Uncertainty.
• Sledge GW Jr. (2016). Curing Cancer: Reality or Myth? Journal of Clinical Oncology.
• Ioannidis JPA. (2005). Why most published research findings are false. PLoS Medicine. (Critical study on interpreting medical data).
• Mayo Clinic. Understanding Cancer Prognosis: Statistics vs. Reality.