Martin Eklund

Martin Eklund

Professor | Docent
Telephone: +46852482501
Mobile phone: +46737121611
Visiting address: Nobels väg 12a, 17165 Solna
Postal address: C8 Medicinsk epidemiologi och biostatistik, C8 MEB Eklund, 171 77 Stockholm

About me

  • I am professor of epidemiology at the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet (KI). I did all my undergraduate studies at Uppsala University, apart from a three-semester stint at the University of Otago in Dunedin, New Zealand, where I studied mathematics and biotechnology. I also did my PhD at Uppsala University, mainly focusing on computer intensive methods for statistical model choice and validation.

    After finishing my PhD, I moved on to postdoc positions at the section for Global Safety Assessment at AstraZeneca and at the Department of Medical Epidemiology and Biostatistics, KI. During 2013 and 2014, I was based in San Francisco and worked at the Department of Surgery, University of California San Francisco (UCSF).

    Since 2015, I am based at MEB where I focus my research on reducing the mortality of breast- and prostate cancer as well as the negative side effects of today’s imprecise diagnostics and treatment selection. To achieve this, I have together with a fantastic team of national and international colleagues, coworkers, and collaborators constructed research programs spanning across biomarker development, validation and implementation, prediction modeling and artificial intelligence, translational medicine, and clinical trials.


  • My research aims to reduce breast- and prostate cancer mortality through the use of individualized prevention, diagnostics, and treatment.

    === Prostate cancer ===


    The prostate-specific antigen (PSA) test is used to screen for prostate cancer but has a high false-positive rate that translates into unnecessary prostate biopsies and overdiagnosis of low-risk prostate cancers. STHLM3 ( was a large-scale prospective and population-based prostate cancer diagnostic trial involving close to 60, 000 men in Stockholm 2013-2015 with the aim of to develop and validate a model to identify high-risk prostate cancer with better test characteristics. The two screening methods, PSA and the Stockholm3 test, were assessed and compared for safety and efficacy. The primary aim of the STHLM3 trial was to investigate if the Stockholm3 test could substantially reduce the proportion of men undergoing prostate biopsy whilst maintaining the sensitivity for detecting consequential prostate cancer (Gleason Score 7 or above) compared to PSA. The results showed that the Stockholm3 test could reduce the number of unnecessary prostate biopsies by close to 50% and decrease indolent cancers (Gleason 6, typically regarded as overdiagnosed cancers) by 20%, without reducing the sensitivity to detect consequential prostate cancer compared to using the PSA. The data from the trial provides a fantastic resource for studying prostate cancer diagnostics, and has since the publication of the main results in the Lancet Oncology 2015 been used in a large number of follow-up publications.


    We are currently conducting the STHLM3-MRI trials (NCT03377881). That MRI improves prostate cancer diagnostics has become clear over the last few years. During 2016 and 2017, we performed the “STHLM3 MRI Phase 1 – A paired diagnostic trial”, where we included 723 men referred for a prostate biopsy at six centra (4 in Stockholm and 2 in Norway). Stockholm-3 combined with MRI was shown to decrease both unnecessary biopsies and overdiagnosis by about 50% and at the same time increase the sensitivity for consequential prostate cancer (Gleason score ≥ 7) compared to using systematic biopsies on all men. The second stage of the STHLM3-MRI research program was conducted 2018-2020, where we assessed the combined use of risk prediction using the Stockholm3 test together with MRI and targeted biopsies in a large-scale (N=12, 750) prospective and population-based randomized screening-by-invitation setting. The aims of the trial was to shown improved specificity and reduced detection of clinically insignificant disease in early detection of prostate cancer without decreasing the sensitivity of clinically significant prostate cancers by combining the Stockholm-3 prediction model together with MRI and targeted prostate biopsies. The first papers from this trial were published in NEJM and the Lancet Oncology, respectively. In these manuscripts, we show that MRI with targeted and standard biopsy in MRI-positive men was noninferior to standard biopsy for detecting clinically significant prostate cancer, and markedly reduced detection of clinically insignificant cancer. The reduced rates of unnecessary biopsy and diagnosis of clinically insignificant cancer address key barriers impeding implementation of population-based screening for prostate cancer. We further demonstrated that the Stockholm3 prostate test can inform risk stratification before MRI and targeted biopsies in prostate cancer screening.

    AI assisted prostate cancer pathology

    Histopathological evaluation of prostate biopsies is critical to the clinical management of men suspected of having prostate cancer. Despite this importance, the histopathological diagnosis of prostate cancer is associated with a number of challenges: The large number of prostate biopsies being performed worldwide together with the shortage of well-trained uro-pathologists and the high inter- pathologist variability leads to suboptimal prostate cancer diagnostics and prognostication, with risks for under- and overtreatment. We have over the last years developed an artificial intelligence (AI) system to assist the pathologists in the evaluation of prostate biopsies, with the overarching aim of solving these problems. In articles published in the Lancet Oncology in 2020 and Nature Medicine 2022, we demonstrate that the system performs on par with internationally leading uro-pathologist for grading prostate needle biopsies. We are now working on further developing the AI system, in particular by:
    1. Performing retrospective international multisite validation of the AI system to assess and improve the AI’s performance across different labs, technical platforms, and disease subtypes
    2. Developing methods to go beyond today’s grading to improve prognostication
    3. Linking the AI system with genomic profiling of tumor tissue to improve treatment selection
    4. Performing prospective validation of the AI system in a randomized diagnostic histopathology trial (scheduled to start early 2024).


    Conservative management with active surveillance of men diagnosed with low-risk prostate cancer includes serial testing with PSA tests and systematic prostate biopsies for disease progression to offer selective delayed treatment with curative intent. A drawback with current active surveillance is the large number of prostate biopsies the men undergo, which leads to reduced adherence to follow-up biopsies with the risk of missing the curative window of progressing disease. In addition, biopsies increase the risk of severe infections. The objective of the prospective STHLM3-AS trial was to assess a less invasive and more cost-effective way to detect clinical significant prostate cancer in men on active surveillance including an improved blood-based Stockholm3 test for identification of men with increased risk of upgraded prostate cancer and use of MRI to select men for diagnostic workup with targeted prostate biopsies. The main results from the trial was published in JNCI in 2021.


    Approximately 30% of men diagnosed with prostate cancer develop lethal metastatic castration-resistant prostate cancer (mCRPC). Although recently approved new drugs are beneficial for many mCRPC patients they carry three serious disadvantages. First, these drugs are all very expensive. Second, the response rates to these drugs are low, ranging between 20-40%. This leads to suboptimal treatment and unnecessary side-effects. Third, there are no predictive treatment markers available in clinical care today, which leads to ineffective trial-and-error in treatment decisions. Our hypothesis is that treatment decisions based on molecular profiling will significantly increase progression free survival compared to current clinical care. The vast majority of CRPC metastasize to the bone, with low success rate in obtaining sufficient material. Therefore, we sequence circulating tumor DNA (ctDNA) consisting of DNA debris from apoptotic cancer being present at high levels in plasma. We are currently testing this hypothesis in the ProBio trial, a large, international, multicentre, randomized study in men with mCRPC that started in 2018. ProBio (NCT03903835) uses an outcome-adaptive randomization trial design, with the goal to learn as rapidly as possible which treatments are effective for which ctDNA biomarker profiles. We are currently working on extending the ProBio platform trial to also encompass men with metastatic hormone sensitive prostate cancer (mHSPC). The design and objectives of the ProBio trial have been described in a publication in Trials in 2020.

    === Breast cancer ===

    The WISDOM trial

    The WISDOM trial ( investigates whether a risk-based approach to breast cancer screening is as safe and effective as annual mammograms. We will also determine whether women readily accept personalized screening and if knowledge of their own risks, and the reasons for less-frequent screening, will reduce anxiety about breast cancer. Finally, we will determine whether our personalized approach will lead to more of the highest-risk women deciding to use strategies that can prevent breast cancer. Participants in the personalized screening arm receive a risk assessment that includes family and medical history, breast density measurement, and genomic tests (SNPs and high-penetrance genes such as BRCA1/2). WISDOM is currently enrolling and will in total enroll 65, 000 women across sites covering the entire US. WISDOM is funded by the Patient Centered Research Outcomes Institute (PCORI) and NIH. We have described the design and objectives of WISDOM in a string of publications (see e.g. JNCI and JNCI Cancer Spectrum).


    The KARISMA trial was a six-armed randomized, double-blinded, placebo controlled study that started in November 2016 and finished in 2020 to investigate the effectiveness of different doses of Tamoxifen to reduce mammography density, with the aim of improving breast cancer prevention. The purpose of KARISMA is to identify the lowest dose of Tamoxifen being within the equivalence limits of 20 mg Tamoxifen arm and to determine dose dependent adverse events and quality of life. Our hypothesis was that a lower dose of Tamoxifen has non-inferior ability to prevent breast cancer as a 20 mg dose, but results is markedly less side effects and is therefore more readily acceptable by women. The main results from the trial was published in JCO in 2021, and several follow-up manuscripts are currently being written.

    === Other diseases and conditions ===


    The goal of the I-SPY COVID trial is to rapidly screen promising agents, in the setting of an adaptive platform trial, for treatment of critically ill COVID-19 patients. In this phase 2, open label, randomised platform design, we aim to identify agents with a signal suggesting a big impact on reducing mortality and the need for, as well as duration, of mechanical ventilation. There are numerous potential effective therapies that warrant testing in clinical trials. Although several therapies are under investigation, each trial is a one-off effort, many are not randomized, and there is no coordinated rapid cycle learning. An adaptive platform trial is the ideal design, as it allows the rapid screening of many agents simultaneously. The study design features comparison of investigational agent efficacy using a Bayesian design against current standard of care (including remdesivir+dexamethasone as backbone therapy). The trial started in July 2020 and is accruing patients across 35 sites in the United States. The trial rationale is described in a recent publication in Nature Medicine.

    Proximal hamstrings avulsions

    PHACT is an international, prospective, multicentre, randomized controlled trial comparing operative to nonoperative treatment of proximal hamstrings avulsions. The aim of PHACT is to obtain reliable evidence for the effectiveness of the two basic treatment options (surgical versus non-surgical treatment) for patients with total proximal hamstrings avulsions. Our primary aim is to compare the patient reported functional outcome, as measured by the Perth hamstrings assessment tool (PHAT), of surgically treated hamstrings avulsions compared to non-operative treated ruptures. The primary outcomes of the study are the PHAT scores 24 months.

    === Group members ===

    Nita Mulliqi (PhD student)
    Hari Vigneswaran (PhD student)
    Kelvin Szolnoky (PhD student)
    Joel Andersson (PhD student)
    Xiaoyi Ji (PhD student)
    Chiara Micoli (PhD student)
    Kimmo Kartasalo (postdoc)
    Henrik Olsson (postdoc)
    Alessio Crippa (senior research specialist)
    Thorgerdur Palsdottir (postdoc)
    Andrea Discacciati (statistician)
    Vivekananda Lanka (database developer)
    Geraldine Martinez Gonzalez (research assistant)

    Previous group members

    Matteo Titus (research assistant)
    Álvaro Fernández Quílez (postdoc, now at Stavanger University Hospital, Norway)
    Peter Ström (PhD student, graduated 2020. Now doing AI development in industry)
    Anna Lantz (postdoc, now independent PI)
    Andreas Karlsson (postdoc, now doing AI development in industry)
    Weronika Wrzos-Kaminska (research assistant, now PhD student at EPFL, Switzerland)

    === Current research grants (as PI) ===

    My research is supported by the Swedish Research Council (Vetenskapsrådet), the Swedish Research Council for Health, Working Life and Welfare (FORTE), the Swedish Cancer Society (Cancerfonden), Karolinska Institutet, the European Institute of Innovation &
  • Technology (EIT), Prostatacancerförbundet, Åke Wiberg Foundation, the Stockholm County Council (SLL), the Nordic Cancer Union (NCU), the Patient Centered Research Outcome Institutet (PCORI), and the National Institutet for Health (NIH).


  • I currently teach the course “Multivariable prediction modeling with applications in precision medicine” (LK2990) together with Mattias Rantalainen. In a collaboration Mieke Van Hemelrijck at King's College London, I am also responsible for the course "Clinical Cancer Epidemiology: From Prevention to Treatment and Patient Care".

Selected publications


All other publications



  • Professor, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 2022-

Degrees and Education

  • Docent, Karolinska Institutet, 2013
  • PhD Biostatistics, Uppsala University, 2010
  • MSc Mathematics, Uppsala University, 2006
  • MSc Molecular Biotechnology (civilingenjör), , Uppsala University, 2005
  • BSc Macroeconomics, Uppsala University, 2004

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