Important breakthroughs have contributed to an increased life expectancy for patients suffering from several cancers, such as immunotherapy for melanoma [1], second-generation androgen receptor antagonists for prostate cancer [2] and new drugs for myeloma [3]. However, reduction in cancer mortality has been mostly due to prevention, early detection and improved cancer care organisation [4, 5]. In contrast, approval of anticancer drugs by regulatory agencies gives the impression that new drugs are drivers of cancer care improvement. In fact, they often offer limited benefits to patients while the costs of many new cancer treatments are skyrocketing [6, 7]. In the Netherlands, the nationwide prospective cancer registry revealed a median increment in the survival of patients with advanced solid cancers of little more than 1 month over the past 10 years [8]. With value in health care defined as the outcome of an intervention relative to its related costs [9], many new oncological treatments are thus of limited value [10].

The increasing array of new treatments in oncology can lead to unrealistic patient expectations and, if not duly managed, pushes society to unsustainable health care costs. With the current COVID-19 pandemic-driven increased necessity to make value-based choices in all medical fields, we should critically reassess the value of available cancer care and allow only high-value interventions based on properly designed and conducted trials to reach our practice. In this narrative review, we focus on different factors that likely contribute to the use of low-value oncological treatments. Strategies for preventing the advent of low-value oncological care are presented.

Critical interpretation of clinical trials

Relevant outcomes

The evidence upon which any treatment recommendation is based should ideally come from adequately designed, executed and reproduced phase 3 randomised controlled trials (RCTs). Any treatment should result in clear benefits; improve the chances of a cure or to live longer (increase overall survival [OS]) and better lives (improve quality of life [QOL]) [11]. What absolute OS increase is considered relevant is likely to differ between cultures, age groups and countries. As a frame of reference, to be considered for inclusion on the World Health Organization Model List of Essential Medicines, a cancer drug should increase OS by at least 4–6 months as compared to the standard of care [12, 13]. In contrast, in many modern RCTs leading to drug approvals, median OS improvement is mostly <3 months (Table 1) [14,15,16,17,18,19]. An example was the approval of erlotinib in the treatment of advanced pancreatic cancer that increased OS by 2 weeks when combined with gemcitabine, as compared to gemcitabine alone [20].

Table 1 Overview of major published studies addressing contemporary clinical oncology trials and regulatory drug approvals.

Improving QOL (assessed in trials as patient-reported outcomes [PROs]) should be the main goal of palliative treatment. Since many trials evaluate surrogate primary endpoints (see below), PRO assessments should be thoroughly and correctly conducted to determine whether the studied intervention delivers meaningful benefit [11]. The Consolidated Standards of Reporting Trials (CONSORT) were extended with specific guidelines to increase the consistency of PRO research and reporting [21]. Several studies have shown that PROs are often not studied and, when addressed, adherence to PRO reporting guidelines is often poor (Table 1) [14, 17, 22,23,24,25,26,27].

Clinical benefit scales based on factors such as OS, QOL, toxicity and symptom control have been developed to translate outcome measures to value [28, 29]. Several studies have assessed whether oncology drug approvals meet such society-defined thresholds of clinical benefit. Most studies show <50% meeting these standards (Table 1) [14, 16, 18, 30,31,32,33,34,35,36,37,38].

Surrogate endpoints

Surrogate endpoints, such as progression-free survival (PFS) or response rate (RR), are increasingly used as primary endpoints in phase 3 oncology RCTs (and in non-randomised studies) (Table 1) [14, 18, 19, 39,40,41,42,43,44,45,46,47]. Their use may contribute to effective treatments reaching patients faster (e.g. recent immunotherapy and targeted therapy approvals for advanced lung cancer [48]). However, a recent retrospective analysis showed a limited median time gain of ~11 months when PFS is studied as opposed to OS [49]. Surrogate endpoints are mostly poorly predictive of outcome parameters such as OS [50] or QOL [51]. The use of surrogate endpoints can therefore result in patient exposure to treatments without proper evidence of an effect on a clinically relevant outcome. Such was the case with bevacizumab in breast cancer, receiving approval after one RCT revealed a positive effect on PFS [52]. After repeat RCTs failed to confirm the magnitude of the initial PFS benefit, showed no improvement in OS but demonstrated increased bevacizumab-related toxicity [53, 54], the approval was revoked. Notably, this treatment option is currently still included in the National Comprehensive Cancer Network (NCCN) breast cancer guideline [55]. Introducing new treatments based on surrogate endpoints can lead to incorrect ‘new standards of care’, to which future potential treatments are being compared in costly clinical trials.

Approvals based on non-phase 3 trials

Even though a phase 3 RCT is considered the gold standard for evidence generation, studies spanning more than a decade have demonstrated that a considerable percentage of oncology drug approvals are based on non-phase 3 RCTs [14, 15, 18, 27, 39, 40, 42, 44, 45, 56, 57] (Table 1). Especially, studies leading to expedited approvals often lack active comparators (see ‘regulatory agencies’ below) [58]. For more than half of FDA oncology drug approvals between 2014 and 2019 that were based on single-arm studies, approved therapies already existed to which these should have been compared [59]. Even though subsequent confirmatory phase 3 RCTs are considered obligatory, they are not always performed [42, 43, 47]. When confirmatory trials do address OS as the primary outcome, these often do not show benefit [47]. A recent example was the approval of olaratumab for treatment of advanced sarcoma in combination with doxorubicin based on a 14-month survival increase in a single open-label phase 1b and phase 2 trial [60]. Resources were wasted on a treatment, of which the results of the ensuing phase 3 RCT failed to show OS improvement [61].

Single RCTs

A new treatment should ideally be approved after demonstrating benefit in a repeated clinical trial. In general, a second positive RCT is considered to confirm the effectiveness of the tested intervention. This is of importance as even with detection of a statistically significant difference between treatment arms in an RCT, there is the possibility of the finding being false positive [62]. Single RCTs are, however, increasingly considered sufficient to lead to drug approvals. A recent study reported that, of 120 FDA approvals (2014–2019), 117 were based on a single RCT [57].

An initially detected effect of an intervention in an RCT is often smaller when the trial is repeated or reanalysed, and large treatment effects in small RCTs are usually not reproducible [63,64,65]. A recent study showed that post-approval updates of RCTs in breast, lung and prostate cancer show a decrease in the initially detected and reported effect upon which the approval was based [66]. The ‘fragility index’, which is the minimum number of changes from non-events to events causing an RCT to lose statistical significance, could be calculated in 17 of 36 oncology RCTs [67]. An outcome change of a mere two events would have 53% of these 17 RCTs lose statistical significance, casting doubt on their robustness. The chance of a properly conducted RCT being false negative is very small (based on the a priori probability of an intervention being effective and the generally accepted threshold of false negativity in RCTs of 20% (power of 80%)). Taking this all together, drug approvals after a single RCT may be based on false positive, exaggerated and/or ‘fragile’ findings.

Non-representative for everyday practice

In clinical trials, the selected population and the context of care delivery are commonly not representative of the general patient population or everyday practice. Fit and relatively young patients are included and intensively monitored during treatment [11]. Even though carrying a higher cancer burden, minorities [68] and older patients [23] are often underrepresented, limiting the broad representability of trial findings. The benefit detected in a clinical trial is usually less and toxicity greater in everyday practice, especially in patients who do not fulfil the original inclusion/exclusion criteria of the respective clinical trial. For example, in ‘real-life data’ in both colorectal cancer [69] and prostate cancer [70], it was observed that treatment outcome was worse than expected in patients not fulfilling the original trial inclusion criteria. A recent study compared trial outcomes of 22 FDA-approved oncology drugs for 29 indications to real-world data obtained in older Medicare beneficiaries [71]. Survival was shorter in Medicare beneficiaries in 28 of 29 indications (median difference −6.3 months, range −28.7 to 2.7 months).

Other important issues in critical evaluation of clinical trials

Many other factors of importance should also be critically assessed when interpreting clinical trials and are beyond the scope of this review. These include the inappropriate use of subgroup analyses [72, 73], the occurrence of inappropriate crossovers [57], the occurrence of informative censoring [74] and the use of inadequate comparator arms [57, 75].

Bias in data publication

Selective or biased reporting in oncological RCTs occurs even in high-impact journals [76, 77]. Spin bias, i.e., misrepresentation of trial findings with the goal of luring readers into believing that the claimed effect is greater than the available data shown, has been reported in almost 60% of RCTs in breast cancer [78] and in 10% of abstracts pertaining to lung cancer trials [79]. Spin bias in abstracts has been shown to influence clinicians’ trial interpretation [80]. It is also directly translated into lay press reporting [81], leading to unfounded expectations of patients, policymakers and physicians [80]. Publication bias, i.e., non-publication or delayed publication of negative studies, needs to be considered whenever we are addressing a potential new treatment (indication), especially since results of non-published studies could be of relevance [82]. Even though the global cancer burden is highest in low- and middle-income countries (LMICs), publication bias by high-impact journals against LMIC oncology RCTs occurs, even as these are more likely to identify high-value therapies [83]. In systematic reviews of cancer trials, publication bias assessments, such as the use of funnel plots, remain underused, which may therefore exaggerate the effects of the reviewed intervention [84]. Harm detected in clinical trials is often underreported [85].

Financial conflicts of interest

Identifying new strategies against disease drives academia and pharma. Aside from academic acknowledgement, funding and promotion of clinical researchers, new treatments, or drug repurposing against both emerging and common diseases, lead to revenue for pharmaceutical companies. However, without industry sponsorship of clinical trials innovation may not reach our patients [86]. Potential financial conflicts of interest (FCI) occur among all stakeholders, investigators and journal editorialists, as well as members of regulatory agencies [6, 87,88,89,90,91]. Studies have shown an association between the likelihood of drug endorsement in consensus guidelines and the FCI of the main author [92, 93].

Regulatory agencies

With the advent of expedited drug approval programmes, regulatory approvals based on limited evidence (e.g. use of surrogate endpoints and non-phase 3 trials) increasingly occur when an intervention serves an ‘unmet clinical need’. This should encompass cancers that have few treatment options with poor disease outcomes [94]. Incorrect use of ‘unmet clinical need’ may, in part, explain the high rate of expedited oncology drug approvals. A recent study showed 95% of 58 FDA approvals from 2012 to 2017 entering an expedited programme [95]. In another study analysing FDA applications for new cancer drugs/indications from 2008 to 2016, 53 of 186 were granted expedited approval [96]. Recently, margetuximab, a monoclonal HER2neu-directed antibody, was granted expedited approval by the FDA for treating advanced breast cancer patients after two prior treatment lines with HER2neu-directed therapy [97]. The drug approval was dated before the publication of the clinical trial [98] and was based on a surrogate endpoint with a PFS benefit of 0.9 months. It is hard to comprehend how, for a disease with many treatment options (next to chemotherapy and hormonal therapy (if applicable) and several FDA-approved HER2neu targeting agents [55]), this would provide in an unmet clinical need warranting expedited approval.

Expedited drug approval pathways require post-approval studies to address evidence gaps. These are often delayed, and if performed, tend to have the same inappropriate characteristics as the pre-approval trials [6, 43, 44, 99,100,101]. A recent overview of 25 years of accelerated approvals of oncology products (all based on surrogate endpoints) showed 51 of 93 initial approvals to confirm benefit in the ensuing years. Thirty-seven (61%) of confirmation studies again used a surrogate endpoint [42]. In another report, for 93 cancer drug indications granted accelerated approval by the FDA, only 20% of confirmatory studies used OS as an endpoint; 41% studied a surrogate with the remaining confirmatory trials not yet reported [43]. Limitations in evidence can therefore persist post approval [102].

Serious side effects may become clear after widespread use after drug approval [85]. For example, real-world post-approval data of ibrutinib, used to treat chronic lymphocytic leukaemia, revealed higher than expected treatment-related cardiac deaths, which may be dose-related [103]. To date, no lower ibrutinib dose trial has been mandated. Another example is the increased risk of myelodysplastic syndrome (MDS) and acute myeloid leukaemia (AML) with the use of poly(ADP-ribose) polymerase (PARP) inhibitors detected in a recent meta-analysis of 28 RCTs and in a study of the WHO’s pharmacovigilance database [104]. This analysis was performed after several cases were detected in the longer follow-up of PARP inhibitor trials. As maintenance PARP inhibitor use in even platinum-sensitive homologous-recombination-proficient ovarian cancer patients has been approved [105], many patients will be exposed to an increased risk of MDS/AML, but with a limited evidence of PFS increase and no proven OS benefit pertaining to their ovarian cancer [106].

Discrepancies between trial inclusion criteria and regulatory agency-approved patient characteristics contribute to the exposure of patients to drugs without supporting data. For example, both enzalutamide [107] and apalutamide [108] were FDA approved for the treatment of men with non-metastatic castration-resistant prostate cancer regardless of prostate-specific antigen (PSA) doubling time, whereas the pivotal trials were limited to men with PSA doubling times of 10 months or less [109, 110]. This broadens prescribing indications to a larger group of lower-risk patients who will be exposed longer to these expensive drugs without proven benefit [111]. A recent study identified 38 approvals (2010–2018) by the FDA, EMA and Pharmaceuticals and Medical Devices Agency; 53% revealed discrepancies between trial inclusion criteria and defined therapeutic indications, and several allow broader prescribing indications [112].

Drug pricing

Conceding the fact that drug pricing, regulatory bodies and financial thresholds for acceptable costs vary between countries, the benefit of many new cancer treatments is in stark contrast to their pricing [7, 113]. No positive association between clinical benefit scales, efficacy or novelty and pricing has been detected [30, 32, 41]. Revenue of approved drugs is such that the need for high drug prices to cover research and development costs may not always be a valid argument [114], especially since the portfolios of pharmaceutical companies overlap, limiting risk and costs of innovation [16, 115].

High drug prices not only lead to cancer treatments being limited to high-income countries but may even delay drugs reaching patients due to unavoidable time-consuming price negotiations [116]. Financial constraint is one of the main determinants of health care availability. With increasing drug prices, even in affluent countries, financial limitations influence cancer drug availability [13, 117].

Raising the bar

Several recommendations can be made that could all contribute to raising the bar in oncology (see Box 1). The first important step is the recognition of the scope of the problems depicted above. The explosive increase in publications on new treatments renders oncologist’s dependent on rapid reading services, abstract reading and expert opinion regarding evidence assessment. A recent study showed that clinicians often overestimate the benefit and underestimate the harm of medical interventions [118]. Unrealistic patient expectations of ‘breakthrough treatments’ [11, 95] occur as a result of direct-to-consumer marketing with a poor translation of scientific data by lay press [81], cancer centres [119] and treating physicians [120, 121]. Medical education needs to be transformed so that we are better prepared for the broader responsibilities and social aspects of modern-day medicine, data interpretation, research and value-weighted treatment selection.

Educational focus on a ‘less is more’ principle for managing patients with advanced cancer should contribute to raising the bar. By adhering to QOL standards, the value of early palliative care with timely refrainment from anticancer therapy should be an integral part of oncology training. Patients suffering from advanced cancer are willing to undergo toxic treatments with a very small chance of benefit near the end of life [122]. However, systemic anticancer treatments often provide limited or no benefit to patients suffering from advanced cancer [123], lead to harm in the last weeks of life, reduce QOL, limit timely hospice care and increase risk of dying in the hospital with subsequently an increased risk of pathological grievance of bereaved [124, 125]. Informing patients of treatment effects in daily practice by quoting point estimates, such as median OS achieved in highly selected patients from RCTs instead of using ‘real-life data’ (if available), could contribute to unrealistic patient expectations [126]. Accurately disclosing prognostic information does not negatively impact patient–physician relationships but may skew low-value life-prolonging care to comfort-oriented care [127]. Therefore, translating complex trial and real-life data to daily clinical practice and adequately and understandably communicating this to patients should receive appropriate attention in oncology training.

Both the medical scientific society and regulatory agencies should aim at improving the quality of clinical trials. The use of surrogate endpoints should be limited to those for which evidence exists of their validity (e.g. metastasis-free survival in localised prostate cancer [128]). Head-to-head comparisons of new drugs and use of the standard of care in control arms should be the norm instead of comparing many new ‘same class’ drugs to inappropriate control arms. Lowering the arbitrary p ≤ 0.05 for rejection of the null hypothesis in RCTs has been proposed as a possible strategy to reduce the risk of false-positive results at the cost of occasionally missing a true and clinically relevant treatment effect [129, 130]. Either the p value for positivity should be lowered or trial replication should, whenever possible, be mandatory before regulatory approval and inclusion into guidelines.

Regulatory agencies should mandate not only confirmatory trials after rapid approvals but should also critically address post-marketing safety concerns. Expedited approval processes should be limited to indications for true unmet clinical needs. When approving drugs, both regulatory agencies and medical societies should adhere to indications as studied, thereby limiting unwarranted prescribing. Retraction of drug approvals should be followed by guideline retractions.

Bias in journal reporting should be eliminated and all data should be available at the time of issuance of both regular approvals and expedited approvals [131]. Data should be presented in a more palatable manner for both physicians and the lay press by employing measures such as absolute risk reductions, number needed to treat and number needed to harm [132]. When applicable, reporting the fragility index, as an indication of trial data robustness, should be considered [67]. Concluding statements in abstracts should be simple and clear and strictly relate to the primary endpoint. Stating FCI’s to readers and audiences should be mandatory, but FCI’s should ideally be avoided.

Our societal responsibility transcends oncological care. Implementation of costly low-value oncological treatments invariably impacts health care accessibility in other medical fields. At least in our country, for the price of one pembrolizumab dose administration [133], four type 1 diabetes mellitus patients can use a flash glucose monitoring system for almost a year to better manage their disease [134], against which they face a lifelong battle. We should, as health care advocates, scrutinise drug pricing and aim for fair distribution of health care spending. Concerted efforts are needed at all levels (physicians, clinical researchers, medical societies, drug companies, regulatory agencies, payers and politicians) for this to be effectively addressed. Integration of value-based scales into regulatory agency policies should raise the bar for drug approvals as well as influence drug pricing and availability. As oncology drugs may often be dosed higher or more frequently than needed, lower doses, alternate dosing schedules and shorter treatment times should be studied [135]. Efforts have been initiated to reduce the use of inappropriate tests, treatments, procedures and costs in oncology, such as the ‘Choosing Wisely’ initiative [136].

The COVID-19 pandemic has impacted health care resources urging the medical community to increasingly adhere to only high-value health care interventions in all medical fields. Strictly selecting high-value cancer care should carry momentum in the oncology landscape far beyond this world disruptive event.