Cancer doesn't just arrive with a diagnosis—it arrives with uncertainty.
Health insurance is meant to bring certainty in moments of chaos. But when it comes to cancer, most people discover that coverage is only part of the story. Bills stack up. Paperwork multiplies. Approvals take time. And every delay adds another layer of stress — financial and emotional.
At Plum Datalabs, we wanted to look beyond policy brochures and claim forms to understand what the real cost of cancer looks like — not just in rupees, but in experiences. How much do patients actually pay? How much does insurance cover? How many times do families go through the cycle of hospital visits, pre-authorisations, and reimbursements?
It's a data-driven investigation into one of the most complex, life-altering diseases — seen through the lens of 8,102 insurance claims across multiple insurers.
Early detection of cancer has increased by 72% over the last three years.
We're observing a surge in in-situ carcinoma cases over the last three years, indicating that cancer is being detected in the earlier stages before it becomes invasive.
Note: Carcinomas in situ is an early-stage condition where abnormal cells are confined to the tissue layer where they first formed and have not yet spread to surrounding areas. It is also known as 'stage 0 cancer' and is considered non-invasive. While not yet invasive, the abnormal cells may eventually become cancerous, which is why early detection and treatment are crucial for preventing them from developing into invasive cancer.
Breast Cancer Leads the Malignant Burden.
Among malignant cancers, breast cancer stands out as the leading type and is overwhelmingly female‑predominant. Even when gender‑specific cancers are set aside, clear patterns remain: several high‑incidence cancers skew male (such as lung and head & neck), shaped by exposure and behavior. Keep this lens in mind as we examine costs and care pathways.
When do different types of cancers manifest?
This horizon chart illustrates how various cancers impact different age groups. Each row represents a cancer type, with color intensity showing claim volume across age ranges. Notice how some cancers like testicular cancer concentrate in young adults, while prostate cancer only appears after age 50.
We observe two concerning patterns. First, a relatively high incidence of blood cancers among infants warrants deeper investigation. Second, there is an earlier onset of cancers among individuals in their 20s — especially liver, bone, and testicular cancers. An illness traditionally associated with older age is increasingly manifesting among younger, working‑age Indians.
Treatment Complexity Determines the Years of Household Savings Lost
We analyzed cancer claims by Treatment Intensity Levels (TIL) — a measure that captures the overall treatment journey, including the number of claims, hospital admissions, total expenses, treatment duration, and variety of medical procedures.
This helped us understand how the financial burden of cancer increases with treatment complexity (TIL I–IV).
In the Indian context, where a typical household saves about ₹1,00,000 a year, patients in higher intensity tiers (TIL III and IV) face a median treatment cost of ₹7.6 lakh — effectively erasing 7–13 years of household savings, and in extreme cases, up to 20 years.
Blood, brain and colorectal cancers drive the highest costs.
Blood cancers (leukemia, lymphoma) and brain cancer consistently push the highest percentage of patients into the ₹10L+ cost bracket. Liver and pancreatic cancers also show heavy concentration in higher cost brackets. Not all cancers cost the same—this pattern reveals where patients need the most financial protection.
Surgery Dominates Cancer Treatment Claims, But Patterns Vary by Type.
Cancer treatment varies dramatically by type, reflecting fundamental differences in disease biology and therapeutic approach. Colorectal, brain, and stomach cancers are the most financially intensive, while stomach and ovarian cancers require the most frequent medical engagement. Care settings also differ. Blood and lymph cancers demand heavy hospitalization, while breast and stomach cancers rely on daycare chemotherapy. Brain cancers stand apart for their diagnostic complexity, requiring substantially more imaging and testing than other malignancies. These patterns reveal that cancer treatment isn't uniform—each type follows distinct pathways shaped by where the disease occurs and what interventions work best.
The Tail End of Cancer Costs: Extreme Variations Reveal Hidden Burdens.
While median costs provide a baseline, the tail end of the cost distribution reveals extreme variations. Some patients face costs 5-10x higher than the median, highlighting the unpredictable financial burden of cancer treatment. This analysis focuses on these outliers—the patients who bear the heaviest economic weight.
Cost Scenarios
We analyse five cancer patient journeys to depict the actual burden of cancer across treatments and cost.
1 in 4.7 patients exceed their ₹5L insurance limit.
While 39.5% of cancer patients stay within ₹1.25L in treatment costs, a significant portion—21.4%—exceed ₹5L, pushing them beyond their typical sum insured coverage and into catastrophic financial territory.
| Cost Range | % of Patients | Avg Claims |
|---|---|---|
| 0 to ₹1,25,000 | 39.5% | 1.5 |
| ₹1,25,000 to ₹2,50,000 | 19.5% | 2.6 |
| ₹2,50,000 to ₹3,75,000 | 11.8% | 4.2 |
| ₹3,75,000 to ₹5,00,000 | 7.8% | 4.7 |
| ₹5,00,000+ | 21.4% | 7.4 |
Insurance payouts are decreasing.
Over the last three years, the deduction rate for cancer-related claims has increased by 58%. This trend shows a concerning pattern where insurance payouts are becoming less reliable, leaving patients with higher financial burden. The cancers that require the highest treatment costs often receive the lowest payout percentages, forcing patients to bear significant out-of-pocket expenses.
Why does cancer show such high rates of deduction?
Understanding the root causes behind high deduction rates helps patients navigate the insurance landscape more effectively. Several systemic factors contribute to this problem.
Off-label Drug Approvals
New cancer drugs with US FDA approval may still be considered 'off-label' in India. Many standard plans exclude or limit coverage for these drugs, making this the most common reason for claim rejections.
50% Sub-limit on Modern Treatments
Modern treatments like oral chemotherapy are subject to a 50% sub-limit. Even when covered, insurers only pay half the cost.
Other Policy Exclusions
Multiple exclusionary clauses reduce coverage: pre-existing condition waiting periods, room rent capping, co-payments (10-20% of claims), and exclusion of 'experimental' procedures even if they're standard treatments.
DataLabs by Plum · The Cost of Cancer · In short
Key findings
- In Plum's cohort of 8,102 cancer-related insurance claims across multiple insurers, which includes carcinoma in situ and benign growths such as fibroids, ₹78.0 crore was claimed in total, insurers paid 70.8% of the amount claimed, and patients' out-of-pocket costs came to ₹23.2 crore.
- Of the 2,431 patients in Plum's cancer treatment-intensity analysis, 20.2% (about 1 in 5) had total claimed treatment costs above ₹5 lakh, the edition's figure for a typical annual sum insured, while 39.7% stayed within ₹1.25 lakh.
- In Plum's cancer claims data, the median total amount claimed per patient, before insurance payouts, was ₹7.6 lakh at Treatment Intensity Level III (157 patients) and ₹13.4 lakh at Level IV (14 patients), which the edition equates to 7.6 and 13.4 years of savings for a household that saves ₹1,00,000 a year.
- In Plum's cancer claims data, among the 35 ICD-10 cancer groups in the edition's payout chart, each with 30 or more claims, insurers paid the smallest shares of the amount claimed for myeloid leukaemia (C92, 25.7% across 56 claims), lymphoid leukaemia (C91, 39.5% across 62 claims) and CNS (brain) cancer (C71, 44.0% across 67 claims).
- In Plum's cancer claims data, the share of patients whose claims were for carcinoma in situ (stage 0 cancer that has not spread) was 19.1% in Q1 2023 and 33.0% in Q2 2025, a 72.48% increase that Plum's analysis reads as earlier detection, though the share peaked at 36.4% in Q4 2023 and fell to 23.1% in Q4 2024.
- Breast cancer was the most common malignant cancer in Plum's cohort of cancer-related insurance claims, with 887 claims from 283 patients, and 96.8% of those claims were for women.
- In Plum's cancer claims data, Surgery IPD (inpatient surgery) claims were the largest share of claims for each of the 13 cancer types charted, while chemotherapy daycare claims made up 33.3% of breast cancer claims.
Questions this data answers
How much does cancer treatment cost in India?
In Plum's cancer claims data, 39.7% of the 2,431 patients in the treatment-intensity analysis had total claimed treatment costs within ₹1.25 lakh and 20.2% had costs above ₹5 lakh. Median costs rose with Treatment Intensity Level, to ₹7.6 lakh at Level III (157 patients) and ₹13.4 lakh at Level IV (14 patients). These are amounts claimed from insurers by this insured cohort, not the cost of treatment for all patients in India.
What share of a cancer claim does health insurance pay?
Across the 8,102 cancer-related claims in Plum's cohort, insurers paid 70.8% of the ₹78.0 crore claimed, and patients' out-of-pocket costs came to ₹23.2 crore. Payouts varied by cancer group: among the 35 ICD-10 groups in the edition's payout chart, the lowest payout percentages were for myeloid leukaemia (C92) at 25.7% of the amount claimed, lymphoid leukaemia (C91) at 39.5% and CNS (brain) cancer (C71) at 44.0%. The edition attributes deductions on cancer claims to policy terms such as limits on off-label drugs, 50% sub-limits on modern treatments and co-payments.
How many cancer patients have treatment costs above ₹5 lakh?
Of the 2,431 patients in Plum's cancer treatment-intensity analysis, 20.2%, about 1 in 5, had total claimed treatment costs above ₹5 lakh, the edition's figure for a typical annual sum insured. These patients filed 6.4 claims each on average, against 1.5 for patients whose costs stayed within ₹1.25 lakh.
Which cancers cost the most to treat?
Among the 20 cancer and tumour types with the most patients in Plum's claims data, stomach cancer (6 of 47 patients, 12.8%), colorectal cancer (13 of 125, 10.4%) and leukaemia (4 of 61, 6.6%) had the largest shares of patients whose claimed costs for that cancer type exceeded ₹10 lakh. With so few patients per type, these rankings are indicative only.
Is early detection of cancer increasing in India?
In Plum's insured cohort, the share of cancer patients with carcinoma in situ, stage 0 cancer that has not spread, was 19.1% in Q1 2023 and 33.0% in Q2 2025, an increase of 72.48%, though it peaked at 36.4% in Q4 2023 and dipped to 23.1% in Q4 2024. The share of claims rose less, from 24.1% to 30.5%. Plum reads this as more cancers being caught early in this cohort; it is not a national detection rate.
Which cancer is most common in health insurance claims?
In Plum's cancer claims cohort, carcinoma in situ (stage 0 cancer that has not spread) accounted for the most claims, 2,516 of 8,102. Among malignant cancers, breast cancer was the most common, with 887 claims from 283 patients, 96.8% of those claims for women. Several other common cancers skewed male: 66.8% of lung cancer claims and 77.1% of head and neck cancer claims were for men.
How many insurance claims does a cancer patient file?
In Plum's cohort, patients filed 3.3 claims each on average, 8,102 claims from 2,446 patients. By Treatment Intensity Level, a measure that itself counts claims, the average rose from 1.5 at Level I to 5.5 at Level II, 12.7 at Level III and 22.2 at Level IV, a group of only 14 patients.
At what age do different cancers appear?
In Plum's claims data, there were no prostate cancer claims below age 50, and breast cancer claims peaked at ages 50 to 59, with 374 of 871. Testicular cancer was rare, with 12 claims, 7 of them from people in their 20s. Blood cancers (leukaemia, lymphoma and myeloma) had 58 claims in the 0 to 9 age group.
The data behind the charts
Key figures for the cohort
The three headline figures for the whole cohort of 8,102 claims, as the edition reports them.
| Metric | Value | Note |
|---|---|---|
| Total cost of cancer care | ₹78.0 Cr | claimed in this cohort |
| Patient out-of-pocket | ₹23.2 Cr | what patients actually paid |
| Insurance payout ratio | 70.8% | insurance coverage rate |
In-situ incidence rate by quarter
The share of cancer patients (patient incidence rate) and of cancer claims (claims incidence rate) in each quarter that were for carcinoma in situ, from Q1 2023 to Q2 2025.
• Average patient rate: 29.25% • Average claims rate: 31.91% • Total change (patient): +72.48% • Total change (claims): +26.66%
| Quarter | Patient incidence rate (%) | Claims incidence rate (%) |
|---|---|---|
| Q1 2023 | 19.1 | 24.1 |
| Q2 2023 | 22.5 | 20.9 |
| Q3 2023 | 31.6 | 27.8 |
| Q4 2023 | 36.4 | 36.9 |
| Q1 2024 | 36.0 | 40.2 |
| Q2 2024 | 34.0 | 43.2 |
| Q3 2024 | 30.8 | 33.3 |
| Q4 2024 | 23.1 | 31.1 |
| Q1 2025 | 25.9 | 31.0 |
| Q2 2025 | 33.0 | 30.5 |
Cancer types by gender
For the ten most common malignant cancer types, the share of each type's claims from men and from women, the median patient age for each, and each type's share of the 7,382 malignant cancer claims (incidence).
| # | Cancer type | Incidence (% of malignant claims) | Median age, male (years) | Male (%) | Female (%) | Median age, female (years) | Claims (count) |
|---|---|---|---|---|---|---|---|
| 1 | Breast Cancer | 12.0 | 65 | 1.4 | 96.8 | 47 | 887 |
| 2 | Blood Cancers | 9.8 | 58 | 69.9 | 28.4 | 52 | 721 |
| 3 | Colorectal Cancer | 5.5 | 62 | 58.6 | 41.4 | 59 | 408 |
| 4 | Lung Cancer | 5.0 | 64 | 66.8 | 33.2 | 61 | 371 |
| 5 | Liver Cancer | 4.2 | 58 | 18.6 | 81.4 | 55 | 312 |
| 6 | Head & Neck Cancer | 4.1 | 59 | 77.1 | 21.9 | 54 | 306 |
| 7 | Ovarian Cancer | 3.8 | n/a | 0.0 | 99.3 | 56 | 281 |
| 8 | Stomach Cancer | 2.8 | 63 | 72.1 | 23.6 | 60 | 208 |
| 9 | Prostate Cancer | 2.7 | 68 | 97.5 | 2.0 | n/a | 202 |
| 10 | Gallbladder Cancer | 1.5 | 61 | 67.0 | 33.0 | 58 | 112 |
Male and female shares do not always add up to 100%. "Blood Cancers" combines leukemia, lymphoma and myeloma.
Claims by cancer type and age group
The number of claims for each malignant cancer type in each age group. The chart shades each row from its own lowest to its highest count, so it compares ages within a type, not volumes across types.
| # | Cancer type | 00-09 (claims) | 10-19 (claims) | 20-29 (claims) | 30-39 (claims) | 40-49 (claims) | 50-59 (claims) | 60-69 (claims) | 70-79 (claims) | 80+ (claims) | Total (claims) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 01 | In-Situ Carcinoma | 6 | 5 | 80 | 166 | 325 | 974 | 716 | 223 | 20 | 2515 |
| 02 | Breast | 1 | 0 | 21 | 83 | 148 | 374 | 202 | 42 | 0 | 871 |
| 03 | Blood Cancers | 58 | 17 | 65 | 39 | 33 | 146 | 244 | 96 | 11 | 709 |
| 04 | Colorectal | 0 | 0 | 29 | 17 | 23 | 95 | 183 | 55 | 6 | 408 |
| 05 | Lung | 0 | 0 | 0 | 13 | 9 | 111 | 150 | 78 | 10 | 371 |
| 06 | Liver | 0 | 0 | 144 | 99 | 6 | 31 | 28 | 4 | 0 | 312 |
| 07 | Head & Neck | 0 | 2 | 21 | 28 | 44 | 118 | 74 | 16 | 0 | 303 |
| 08 | Ovarian | 0 | 0 | 13 | 25 | 44 | 118 | 60 | 19 | 0 | 279 |
| 09 | Prostate | 0 | 0 | 0 | 0 | 0 | 32 | 86 | 77 | 6 | 201 |
| 10 | Stomach | 0 | 0 | 4 | 55 | 3 | 25 | 77 | 35 | 0 | 199 |
| 11 | Urologic Cancers | 0 | 0 | 3 | 2 | 4 | 45 | 86 | 22 | 0 | 162 |
| 12 | Biliary & Gallbladder | 0 | 0 | 0 | 55 | 13 | 13 | 47 | 8 | 6 | 142 |
| 13 | Uterine | 0 | 1 | 11 | 20 | 10 | 31 | 28 | 8 | 0 | 109 |
| 14 | Cervical | 0 | 1 | 2 | 4 | 22 | 42 | 13 | 3 | 0 | 87 |
| 15 | Esophageal | 2 | 1 | 1 | 1 | 0 | 40 | 25 | 11 | 0 | 81 |
| 16 | Brain & CNS | 0 | 0 | 7 | 20 | 4 | 13 | 30 | 3 | 0 | 77 |
| 17 | Pancreatic | 0 | 0 | 0 | 0 | 1 | 29 | 29 | 10 | 0 | 69 |
| 18 | Thyroid | 0 | 0 | 13 | 15 | 7 | 7 | 17 | 0 | 0 | 59 |
| 19 | Soft Tissue | 0 | 0 | 3 | 5 | 2 | 5 | 12 | 13 | 0 | 40 |
| 20 | Bone & Cartilage | 1 | 0 | 23 | 1 | 0 | 4 | 0 | 0 | 0 | 29 |
| 21 | Skin | 0 | 0 | 2 | 1 | 4 | 8 | 8 | 2 | 0 | 25 |
| 22 | Skin Cancer | 0 | 0 | 0 | 0 | 2 | 11 | 1 | 0 | 0 | 14 |
| 23 | Testicular | 0 | 0 | 7 | 3 | 2 | 0 | 0 | 0 | 0 | 12 |
| 24 | Small Intestine | 0 | 0 | 1 | 1 | 0 | 4 | 0 | 1 | 2 | 9 |
| 25 | Gynecologic | 0 | 0 | 0 | 0 | 1 | 3 | 2 | 0 | 0 | 6 |
Ages are in years. Rows are sorted by total claims. The chart leaves out benign, uncertain, unspecified, secondary (metastatic) and other broad or ill-defined categories. Brain & CNS, Urologic Cancers (kidney, bladder and other urologic) and Biliary & Gallbladder each combine source categories, and their counts are added together here. "Skin Cancer" is melanoma; "Skin" is other skin cancers.
Years of Savings Lost
The median treatment cost at each Treatment Intensity Level (TIL), expressed as years of household savings at ₹1,00,000 a year, with the interquartile range (25th to 75th percentile) the chart shows as error bars.
| Treatment Intensity Level | Median (years) | 25th percentile (years) | 75th percentile (years) |
|---|---|---|---|
| TIL I | 1.1 | 0.6 | 2.1 |
| TIL II | 4.5 | 3.0 | 6.6 |
| TIL III | 7.6 | 5.1 | 11.1 |
| TIL IV | 13.4 | 10.8 | 22.8 |
Total Cost Distribution
The spread of total treatment cost per patient at each Treatment Intensity Level, which the chart draws as box plots on a logarithmic scale.
| Treatment Intensity Level | Patients (count) | 25th percentile (₹ lakh) | Median (₹ lakh) | Mean (₹ lakh) | 75th percentile (₹ lakh) |
|---|---|---|---|---|---|
| TIL I | 1,664 | 0.58 | 1.09 | 1.65 | 2.14 |
| TIL II | 592 | 2.97 | 4.45 | 5.62 | 6.58 |
| TIL III | 157 | 5.10 | 7.60 | 9.30 | 11.11 |
| TIL IV | 14 | 10.83 | 13.42 | 17.48 | 22.82 |
As in the chart, patients with a recorded total cost of zero are left out. ₹1 lakh is ₹1,00,000.
Treatment Duration Distribution
How long treatment lasted at each Treatment Intensity Level, which the chart draws as violin plots of the full distribution.
| Treatment Intensity Level | Median (days) | Mean (days) | 25th percentile (days) | 75th percentile (days) |
|---|---|---|---|---|
| TIL I | 1.0 | 2.9 | 1.0 | 1.0 |
| TIL II | 1.0 | 29.4 | 1.0 | 36.5 |
| TIL III | 15.0 | 87.4 | 1.0 | 154.0 |
| TIL IV | 188.5 | 195.1 | 28.0 | 232.5 |
Average Claims per Patient
The average number of claims per patient at each Treatment Intensity Level, with the median and interquartile range.
| Treatment Intensity Level | Average claims (count) | Median (count) | 25th percentile (count) | 75th percentile (count) |
|---|---|---|---|---|
| TIL I | 1.5 | 1.0 | 1.0 | 2.0 |
| TIL II | 5.5 | 5.0 | 3.0 | 7.0 |
| TIL III | 12.7 | 12.0 | 10.0 | 15.0 |
| TIL IV | 22.2 | 22.5 | 20.3 | 24.0 |
Treatment Cost Distribution by Cancer Type
For the 20 cancer and tumour types with the most patients, the share of each type's patients whose total treatment cost fell in each cost bracket.
| # | Cancer type | Patients (count) | ₹0-25K (% of patients) | ₹25K-50K (% of patients) | ₹50K-1L (% of patients) | ₹1L-2L (% of patients) | ₹2L-5L (% of patients) | ₹5L-10L (% of patients) | ₹10L+ (% of patients) |
|---|---|---|---|---|---|---|---|---|---|
| 1 | In Situ Carcinoma | 756 | 7.4 | 12.2 | 17.1 | 20.1 | 29.9 | 10.3 | 3.0 |
| 2 | Breast Cancer | 283 | 8.1 | 11.7 | 14.5 | 19.1 | 32.5 | 10.9 | 3.2 |
| 3 | Fibroid | 274 | 4.4 | 6.2 | 25.2 | 38.7 | 24.1 | 1.5 | 0.0 |
| 4 | Liver Cancer | 252 | 2.8 | 24.6 | 45.2 | 20.2 | 2.4 | 2.8 | 2.0 |
| 5 | Benign Tumor | 193 | 17.1 | 17.6 | 24.4 | 16.1 | 14.5 | 7.8 | 2.6 |
| 6 | Colorectal Cancer | 125 | 1.6 | 1.6 | 11.2 | 20.8 | 29.6 | 24.8 | 10.4 |
| 7 | Head and Neck Cancer | 113 | 5.3 | 8.0 | 10.6 | 22.1 | 31.0 | 16.8 | 6.2 |
| 8 | Lung Cancer | 95 | 7.4 | 8.4 | 15.8 | 20.0 | 32.6 | 14.7 | 1.1 |
| 9 | Prostate Cancer | 90 | 4.4 | 12.2 | 15.6 | 18.9 | 27.8 | 20.0 | 1.1 |
| 10 | Ovarian Cancer | 68 | 7.3 | 10.3 | 19.1 | 10.3 | 33.8 | 14.7 | 4.4 |
| 11 | Leukemia | 61 | 14.8 | 8.2 | 18.0 | 13.1 | 24.6 | 14.8 | 6.6 |
| 12 | Non-Hodgkin Lymphoma | 58 | 8.6 | 8.6 | 6.9 | 20.7 | 37.9 | 12.1 | 5.2 |
| 13 | Uterine Cancer | 56 | 10.7 | 19.6 | 16.1 | 17.9 | 28.6 | 3.6 | 3.6 |
| 14 | Multiple Myeloma | 54 | 5.6 | 9.3 | 18.5 | 18.5 | 31.5 | 11.1 | 5.6 |
| 15 | Benign Tumor - Lipoma | 47 | 23.4 | 10.6 | 36.2 | 29.8 | 0.0 | 0.0 | 0.0 |
| 16 | Stomach Cancer | 47 | 12.8 | 8.5 | 19.1 | 10.6 | 27.7 | 8.5 | 12.8 |
| 17 | Neoplasm - Uncertain Behavior | 45 | 15.6 | 11.1 | 15.6 | 17.8 | 28.9 | 11.1 | 0.0 |
| 18 | Secondary Cancer | 39 | 15.4 | 12.8 | 23.1 | 25.6 | 20.5 | 2.6 | 0.0 |
| 19 | Cervical Cancer | 36 | 13.9 | 22.2 | 8.3 | 5.6 | 27.8 | 22.2 | 0.0 |
| 20 | Thyroid Cancer | 35 | 14.3 | 5.7 | 8.6 | 22.9 | 37.1 | 8.6 | 2.9 |
Rows are in order of patient count, and each row adds up to about 100%. K is thousand, L is lakh (₹1,00,000).
Treatment Claims by Modality
For each cancer type, the share of its claims that were surgery or inpatient (IPD) claims, chemotherapy daycare claims, and pre- or post-hospitalisation claims.
| Cancer type | Claims (count) | Surgery IPD (%) | Chemo Daycare (%) | Pre/Post (%) |
|---|---|---|---|---|
| Breast Cancer | 870 | 51.8 | 33.3 | 14.7 |
| Colorectal Cancer (Colon/Rectum) | 408 | 64.7 | 20.6 | 14.7 |
| Lung Cancer | 371 | 59.0 | 26.1 | 14.8 |
| Liver Cancer (Hepatocellular Carcinoma) | 312 | 83.7 | 4.8 | 11.5 |
| Head and Neck Cancer (Oral/Throat/Larynx) | 301 | 53.8 | 27.9 | 18.3 |
| Ovarian Cancer | 276 | 61.2 | 27.9 | 10.9 |
| Multiple Myeloma (Blood & Bone Marrow Cancer) | 206 | 65.5 | 23.3 | 11.2 |
| Non-Hodgkin Lymphoma (Lymphatic System Cancer) | 203 | 66.0 | 21.7 | 12.3 |
| Prostate Cancer | 199 | 57.8 | 21.6 | 20.6 |
| Stomach Cancer (Gastric Cancer) | 199 | 55.8 | 31.7 | 12.6 |
| Leukemia (Blood Cancer) | 167 | 78.4 | 12.0 | 9.6 |
| Gallbladder Cancer | 112 | 37.5 | 36.6 | 25.9 |
| Uterine Cancer (Endometrial Cancer) | 109 | 60.5 | 32.1 | 7.3 |
Rows are sorted by total claims, and each row adds up to 100%.
Treatment Cost Deviation from Median
The chart plots each patient's total treatment cost against how far it sits from the median cost for that patient's cancer type. This table summarises each of the chart's six views instead of listing patients.
| View | Patients shown (count) | Median cost for the type (₹ lakh) | 90th percentile cost (₹ lakh) | Above the median (% of patients) | At least 2x the median (% of patients) |
|---|---|---|---|---|---|
| All Malignant | 1,285 | by type (42 types) | 7.69 | 59.8 | 27.6 |
| Liver Cancer | 181 | 0.75 | 1.86 | 68.0 | 17.1 |
| Breast Cancer | 199 | 1.96 | 6.13 | 58.3 | 26.6 |
| Colorectal | 115 | 3.11 | 10.32 | 51.3 | 25.2 |
| Head & Neck | 89 | 2.26 | 8.69 | 57.3 | 34.8 |
| Lung Cancer | 74 | 1.88 | 5.96 | 59.5 | 27.0 |
The chart shows only patients with a total cost of ₹50,000 or more. In the All Malignant view each patient is compared with the median for their own cancer type. In that view, 71 of the 1,285 patients shown (5.5%) had costs at least 5 times their type's median, and 19 (1.5%) at least 10 times.
Cost Scenarios
We analyse five cancer patient journeys to depict the actual burden of cancer across treatments and cost.
The five patient scenarios, as the edition presents them. The edition's privacy notes describe its personas as composites, not real patient stories.
| Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | Scenario 5 | |
|---|---|---|---|---|---|
| Cancer type | Carcinoma in situ (stage 0) | Gallbladder cancer | Breast cancer | Brain cancer | Leukemia (blood cancer) |
| Patient | 30 years, female | 34 years, male | 39 years, female | 31 years, male | 49 years, female |
| Treatment period | 9.0 months | 20.9 months | 28.4 months | 1.3 months | 4.6 months |
| Hospitalisations (count) | 3 | 19 | 4 | 2 | 6 |
| Chemotherapy cycles (count) | 9 | 14 | 20 | 0 | 1 |
| Pre-post consultations (count) | 6 | 21 | 10 | 0 | 0 |
| Hospitalisation cost (₹ lakh) | 0.99 | 8.69 | 3.90 | 43.68 | 32.61 |
| Chemotherapy cost (₹ lakh) | 4.76 | 1.52 | 5.05 | 0.00 | 7.95 |
| Consultations and tests cost (₹ lakh) | 0.56 | 1.74 | 2.49 | 0.00 | 0.00 |
| Total cost (₹ lakh) | 6.31 | 11.95 | 11.44 | 43.68 | 40.56 |
Treatment Cost Distribution
The share of cancer patients in each range of total treatment cost, and their average number of claims.
| Cost range (₹) | Patients (%) | Average claims (count) |
|---|---|---|
| 0 to ₹1,25,000 | 39.5 | 1.5 |
| ₹1,25,000 to ₹2,50,000 | 19.5 | 2.6 |
| ₹2,50,000 to ₹3,75,000 | 11.8 | 4.2 |
| ₹3,75,000 to ₹5,00,000 | 7.8 | 4.7 |
| ₹5,00,000+ | 21.4 | 7.4 |
Payout Percentage by Cancer Type
The share of the claimed amount that insurers paid (payout percentage) for the 20 cancer groups with the highest payout and the 20 with the lowest, by ICD-10 code. Highest-cost cancers receive payout rates as low as 25–44%, leaving patients to cover 56–75% out-of-pocket.
• Deduction rate increase: 58% (over the last three years, cancer-related claim deductions have increased)
Top 20 (highest payout %)
| # | Cancer type | ICD-10 code | Payout (% of amount claimed) | Claims (count) |
|---|---|---|---|---|
| 1 | Non-Hodgkin Lymphoma | C85 | 85.8 | 69 |
| 2 | Soft Tissue Cancer | C49 | 84.8 | 31 |
| 3 | Carcinoma in Situ | D05 | 81.1 | 463 |
| 4 | Carcinoma in Situ | D02 | 80.7 | 39 |
| 5 | Esophageal Cancer | C15 | 79.8 | 81 |
| 6 | Urinary System Cancer | C67 | 79.7 | 66 |
| 7 | Hodgkin Lymphoma | C81 | 76.3 | 81 |
| 8 | Thyroid Cancer | C73 | 76.1 | 59 |
| 9 | Non-Hodgkin Lymphoma | C83 | 75.5 | 77 |
| 10 | Carcinoma in Situ | D01 | 75.4 | 85 |
| 11 | Lung Cancer | C34 | 74.7 | 357 |
| 12 | Pancreatic Cancer | C25 | 74.7 | 66 |
| 13 | Gallbladder Cancer | C23 | 74.3 | 112 |
| 14 | Carcinoma in Situ | D07 | 73.8 | 38 |
| 15 | Urinary System Cancer | C64 | 73.7 | 45 |
| 16 | Breast Cancer | C50 | 72.0 | 832 |
| 17 | Head and Neck Cancer | C02 | 69.0 | 86 |
| 18 | Ovarian Cancer | C56 | 68.8 | 271 |
| 19 | Biliary Tract Cancer | C24 | 67.4 | 30 |
| 20 | Stomach Cancer | C16 | 67.1 | 199 |
Bottom 20 (lowest payout %)
| # | Cancer type | ICD-10 code | Payout (% of amount claimed) | Claims (count) |
|---|---|---|---|---|
| 1 | Myeloid leukemia | C92 | 25.7 | 56 |
| 2 | Lymphoid leukemia | C91 | 39.5 | 62 |
| 3 | CNS Cancer | C71 | 44.0 | 67 |
| 4 | Head and Neck Cancer | C06 | 51.1 | 55 |
| 5 | Secondary Cancer | C79 | 56.6 | 54 |
| 6 | Primary Cancer Unspecified | C80 | 56.9 | 35 |
| 7 | Cervical Cancer | C53 | 58.7 | 86 |
| 8 | Carcinoma in Situ | D00 | 58.9 | 99 |
| 9 | Colorectal Cancer | C20 | 59.8 | 129 |
| 10 | Prostate Cancer | C61 | 62.4 | 195 |
| 11 | Colorectal Cancer | C18 | 62.7 | 230 |
| 12 | Liver Cancer | C22 | 63.2 | 312 |
| 13 | Multiple Myeloma | C90 | 64.3 | 197 |
| 14 | Endometrial Cancer | C54 | 65.0 | 72 |
| 15 | Carcinoma in Situ | D09 | 66.8 | 1,574 |
| 16 | Stomach Cancer | C16 | 67.1 | 199 |
| 17 | Biliary Tract Cancer | C24 | 67.4 | 30 |
| 18 | Ovarian Cancer | C56 | 68.8 | 271 |
| 19 | Head and Neck Cancer | C02 | 69.0 | 86 |
| 20 | Breast Cancer | C50 | 72.0 | 832 |
5 groups appear in both lists, because 35 groups are ranked in all.
About the data
This edition is built from Plum's de-identified health insurance claims. The cohort is 8,102 claims from 2,446 patients, across multiple insurers. Alongside malignant cancers, it includes 2,516 claims for carcinoma in situ (stage 0, abnormal cells that have not spread) and 778 for benign or uncertain growths such as uterine fibroids, which the charts show as separate types.
Costs come from the claims. Total cost of care is the amount claimed, ₹78.0 crore across the cohort. The insurance payout ratio is the amount insurers approved as a share of the amount claimed, 70.8% overall. Patient out-of-pocket, ₹23.2 crore, is the edition's measure of what patients paid: it tracks the claimed amounts insurers did not approve, so costs that were never claimed are not included, and it is calculated separately, coming to slightly more than total claimed minus total approved (₹22.7 crore). Patient-level figures add up each patient's claims: within each cancer type for the cost brackets by type, so a patient with claims under two types counts in both, and across all of a patient's claims for the Treatment Intensity Levels and the ₹1.25 lakh and ₹5 lakh cost bands.
Treatment Intensity Levels (TIL I to IV) group patients by their whole treatment journey: the number of claims, hospital admissions, total expenses, treatment duration and variety of medical procedures. Most patients are at Level I (1,668 of the 2,431 scored) and only 14 are at Level IV. Years of household savings lost are calculated by dividing a patient's total amount claimed, before any insurance payout, by ₹1,00,000, the edition's figure for what a typical Indian household saves in a year.
Before analysis, DataLabs removes direct identifiers such as names, phone numbers, email addresses and policy numbers. Some views in this edition plot individual patients, such as the chart of each patient's total treatment cost by cancer type. The figures describe this cohort only, and Plum treats the analysis as ongoing: report discrepancies to datalabs@plumhq.com.
- Source
- Plum's de-identified health insurance claims for cancer and related growths, across multiple insurers in India: amounts claimed, insurer payout ratios and patient out-of-pocket amounts by cancer type, with claim counts by age group, gender, treatment modality and quarter, and per-patient costs by Treatment Intensity Level.
- Claims
- 8,102
- Patients
- 2,446
- Insurers
- multiple insurers
- Measures
- amount claimed, payout ratio (share of the claimed amount paid by insurance), patient out-of-pocket amount, cancer type and ICD-10 group, patient age group, patient gender, treatment modality of each claim (Surgery IPD, Chemo Daycare or Pre/Post), claims per patient, treatment duration, Treatment Intensity Level, carcinoma in situ share of patients and claims by quarter
- Published
- 7 November 2025 · updated 13 October 2026
- By
- Ganapathi Ramanathan and Saurabh Arora
How to cite
Ganapathi Ramanathan and Saurabh Arora, “The Cost of Cancer: Financial Impact of Cancer Claims”, DataLabs by Plum, 2025. https://www.plumhq.com/datalabs/cancer
Further reading on plumhq.com
More from DataLabs by Plum
- Investigating Heart Disease: The burden, costs, and early risk: Heart disease in Plum's health insurance claims in India: 9,534 heart-related claims from 7,402 patients, analysed by condition, age, severity and cost.
- All DataLabs editions
For AI assistants: this edition in Markdown · llms.txt.
We show patterns, not people.
Every Datalabs story uses anonymised, aggregated datasets, including claims and health-checkup records where relevant. Before analysis reaches the page, direct identifiers are removed, rare combinations are grouped, and every chart is reviewed so no individual patient, employer, hospital, or policy can be inferred.
- 01
Direct identifiers are removed
Names, phone numbers, email addresses, policy numbers, and other direct identifiers never appear in the analysis or the visuals.
- 02
Only aggregate views are published
We publish cohorts, ranges, medians, ratios, and counts — never row-level records or patient-level timelines.
- 03
Small groups are protected
Rare slices and extreme outliers are grouped, rounded, or excluded whenever a cut could make someone identifiable.
- 04
Examples are composites
Personas are composites used to explain patterns — not real patient stories.
Our goal is to make system-level healthcare economics visible without making any person's health journey identifiable.
This analysis represents our effort to understand and visualize the economic impact of cancer treatment. We've compiled data from thousands of patient records to reveal patterns that might otherwise remain hidden.
While we've worked to ensure accuracy, this analysis is an ongoing process. If you notice any discrepancies or have insights that could improve it, please report them to us.
Talk to us at datalabs@plumhq.com.