A practical guide for teams supporting adults after cancer treatment: digital health products, cancer centres and laboratories, pharma-supported programmes, insurers and employer health programmes.
The US National Cancer Institute considers a person a cancer survivor from the time of diagnosis through the balance of their life, and describes survivorship as the physical, psychological, social and economic experience of life after a cancer diagnosis, for survivors and their caregivers.1 For most people, that experience lasts far longer than treatment itself, and it is where fragmented health data does some of its quietest harm.
The numbers are large and growing. GLOBOCAN 2024, published by the International Agency for Research on Cancer (IARC) in July 2026, estimates 20.6 million new cancer cases and 9.8 million cancer deaths worldwide in 2024, with about 54.2 million people alive within five years of a diagnosis.2, 3 Asia accounts for about half of new cases and more than half of deaths,4 and new cases are projected to reach 34.4 million a year by 2050, an increase of 67% on 2024.2
Source: GLOBOCAN 2024, International Agency for Research on Cancer.
By the time someone finishes treatment, their story is spread across pathology reports, genomic results, chemotherapy and radiotherapy records, imaging, surgical notes and letters from several specialists, often in different hospitals and sometimes different countries. Survivorship care then asks another group of people, usually in primary care, to pick up that story and act on it for years. This guide covers adults after active treatment, using breast and colorectal cancer as examples. Childhood cancer survivors have their own long-term follow-up needs and are outside its scope.
We wrote it for four groups of readers. If you are building a survivorship product, it sets out the data decisions to get right before you scale. If you run a cancer centre, clinic or laboratory, it covers what it takes to hand over a record that others can use. If you lead a pharma-supported programme, it explains what your data needs in order to show outcomes and support real-world evidence. If you are an insurer or run an employer health programme, it shows how survivorship data shapes support for people returning to work and life.
Each source holds part of the story. The value comes from bringing them together in a way that stays accurate for years after treatment ends.
The hardest moment is the handover from active treatment to long-term follow-up. That is where months of detailed oncology records need to become something a different team can read quickly and act on.
The twelve points below are grouped into four themes: getting the clinical picture right, making the data usable, connecting the longer story, and building for trust and scale.
Two decades ago, the Institute of Medicine report From Cancer Patient to Cancer Survivor: Lost in Transition (2005, published 2006) recommended that everyone completing primary cancer treatment receive a comprehensive care summary and follow-up plan, clearly explained.5 The American Society of Clinical Oncology (ASCO) publishes treatment summary and survivorship care plan templates, including disease-specific versions.6
For a data product, the treatment summary is the foundation everything else rests on: the diagnosis and stage, the surgery performed, the medicines given (with doses and dates), radiotherapy details, and the follow-up plan. Many survivorship tools ask people to reconstruct this from memory, which is exactly the information they are least able to give accurately.
What good looks like: a structured treatment summary, built from source records rather than self-report, with each element dated and traceable to the document it came from.
Matters most to: Startups, Cancer centres and laboratories, Insurers and employers
Cancer stage is usually recorded using the TNM system (tumour, node, metastasis), and the rules change between editions. The Union for International Cancer Control (UICC) published the ninth edition of its TNM classification in 2025. The American Joint Committee on Cancer (AJCC) now updates staging one cancer site at a time as "Version 9", with the eighth edition rules still current for sites not yet revised.7, 8
A stage recorded without its edition can mean different things in different records, and survivors diagnosed years apart may have been staged under different rules.
What good looks like: stage stored as its separate T, N and M components, with the staging system, edition or version, and whether it was clinical or pathological staging.
Matters most to: Cancer centres and laboratories, Pharma programmes
A general "breast cancer" or "colorectal cancer" label hides the detail that shapes survivorship care. The International Classification of Diseases for Oncology (ICD-O, currently ICD-O-3.2) is used by cancer registries to code both the site of a tumour and its histology, meaning the type of cells involved.9 Two people with "breast cancer" can have very different diseases, treatments and follow-up needs.
What good looks like: diagnoses coded for both site and histology, with laterality and date of diagnosis, mapped to medical coding standards so they can be compared across sources.
Matters most to: Cancer centres and laboratories, Pharma programmes
The pathology report is the most important document in a cancer record, and one of the hardest to use. The International Collaboration on Cancer Reporting (ICCR) publishes internationally standardised datasets for cancer pathology reporting, and the College of American Pathologists publishes cancer protocols with electronic structured versions.10, 11 Yet many reports, especially older ones and those from smaller laboratories, remain narrative text, scanned documents or PDFs, sometimes in different languages.
What good looks like: pathology reports turned into structured findings (tumour type, grade, size, margins, lymph node status) aligned with recognised reporting datasets, with clinical review and the original report kept alongside.
Matters most to: Cancer centres and laboratories, Startups, Pharma programmes
Hormone receptor status, HER2 (human epidermal growth factor receptor 2), inherited gene variants such as BRCA, and next-generation sequencing results guide treatment and, for some people, their family's screening. Reporting is far from uniform. A study of 21 academic laboratories found that the criteria, schemes and formats used to report genomic results vary greatly, which can affect the consistency of cancer care.12
What good looks like: each biomarker stored with its test method, scoring system, laboratory and date, genomic variants recorded in a consistent format, and inherited results flagged for their relevance to family members.
Matters most to: Pharma programmes, Cancer centres and laboratories
Some treatments carry risks that appear years later. Anthracycline chemotherapy, HER2-targeted therapy and chest radiotherapy, for example, can affect the heart. The 2022 European Society of Cardiology (ESC) cardio-oncology guidelines, developed with haematology, radiation oncology and cardio-oncology societies, recommend cardiovascular risk assessment before treatment and, depending on risk and treatment, heart scans during and after it, including echocardiography at one, three and five years after anthracyclines for survivors at high risk.13
This only works if the record holds the exposure details: which medicines, at what cumulative dose, and what radiation reached the heart.
What good looks like: treatment exposures stored with agents, cumulative doses and radiotherapy details, linked to the monitoring they trigger, with heart scan results held in the same record.
Matters most to: Startups, Cancer centres and laboratories, Pharma programmes
Follow-up after curative treatment often follows a defined schedule of tests and scans. For colorectal cancer, for example, guidance endorsed by ASCO recommends carcinoembryonic antigen (CEA) blood tests every three to six months for five years, and chest and abdominal computed tomography (CT) scans every year for three years.14 Tumour marker results are only useful as trends, measured consistently, and a missed test is information in its own right.
What good looks like: surveillance schedules linked to each person's cancer type and treatment date, tumour markers stored with units and laboratory, and missing tests flagged as gaps rather than read as normal.
Matters most to: Cancer centres and laboratories, Startups
Some survivors take treatment for years after the main phase ends. Adjuvant endocrine therapy for hormone receptor positive breast cancer, such as tamoxifen or an aromatase inhibitor, is typically taken for five to ten years.15 Gaps and early stopping are common: in one US cohort of insured women, fewer than a third were still taking it without significant gaps by year five.16 Side effects, costs and changing providers all contribute, and the reasons are rarely recorded.
What good looks like: long-term medicines recorded with start dates, planned duration, refill patterns and reasons for any change, mapped to medical coding standards and linked to reported side effects.
Matters most to: Pharma programmes, Startups
Much of what matters to survivors never appears in a laboratory result: fatigue, pain, cognitive difficulties, anxiety, low mood and fear of recurrence. Validated patient-reported outcome measures exist for this. The European Organisation for Research and Treatment of Cancer QLQ-C30 questionnaire covers physical, cognitive and emotional function and symptoms such as fatigue and pain, and is validated in more than 120 languages.17 ASCO guidance on anxiety and depression in adult survivors recommends screening with established tools such as the PHQ-9 (Patient Health Questionnaire) and GAD-7 (Generalized Anxiety Disorder scale).18
What good looks like: validated measures recorded by name and version, collected at a sensible cadence, protected with stricter access, and linked to clear pathways to support.
Matters most to: Startups, Pharma programmes, Insurers and employers
Survivorship care often moves between oncology and primary care, and studies document gaps in communication and unclear responsibility between them.19 The stakes are real: survivors have a higher risk of developing a new, unrelated cancer, around 14% higher than the general population in a large US registry analysis,20 so screening and symptom review remain important long after the first cancer.
A useful summary gives the next clinician the treatment summary, current surveillance status, late effects monitoring, long-term medicines and recent patient-reported outcomes in one view. New or persistent symptoms and rising tumour markers need clear rules, agreed with the treating team, that direct the survivor or clinician to act.
What good looks like: a shared summary that oncology and primary care can both read, a named owner for each follow-up task, and escalation rules agreed with clinicians and tested.
Matters most to: Cancer centres and laboratories, Insurers and employers, Startups
Software intended for a medical purpose, without being part of a hardware device, is described internationally as Software as a Medical Device.21 Survivorship tools cross into this territory when they triage symptoms, predict an individual's risk of recurrence or late effects, or recommend changes to treatment or surveillance. Regulators in Singapore, the UK, the European Union, Australia, the United States and many other markets each apply their own rules.
What good looks like: an intended purpose written down early, claims reviewed against the rules in each market you serve, and validation evidence gathered from the start rather than retrofitted.
Matters most to: Startups, Pharma programmes
Cancer records are among the most sensitive health data there is, and genetic results carry implications for family members as well as the person tested. This data is protected under laws such as the EU General Data Protection Regulation (GDPR), Singapore's Personal Data Protection Act (PDPA) and, where it applies, the Health Insurance Portability and Accountability Act (HIPAA) in the United States. People returning to work need confidence that information shared for their care or wellbeing will not be used against them by employers or insurers.
Survivorship lasts a lifetime, and records need to move with people. Oncology-specific interoperability profiles already exist, such as mCODE (minimal Common Oncology Data Elements), an implementation guide for FHIR (Fast Healthcare Interoperability Resources) published by HL7 International.22
What good looks like: granular consent recorded alongside the data, extra protection for genetic results, clear separation from employment or underwriting decisions, pseudonymisation for secondary use, and export in standard oncology formats with provenance intact.
Matters most to: Insurers and employers, Pharma programmes, Startups, Cancer centres and laboratories
You do not need to solve all twelve at once. The right starting point depends on what you are building and what your data needs to do.
Some of the twelve points are data problems, and some are questions of design, strategy and delivery. We support both, so you can come to us with the whole picture rather than splitting it across several partners.
Jonda Health is ISO 27001 certified, and our platform is designed to comply with HIPAA, GDPR and PDPA.
This guide is for teams designing and running digital health tools and programmes. It is not clinical advice for individuals.
