Less Is More? The Long-Term Health and Cost Consequences Resulting from Minimal Invasive Caries Management

Caries is a chronic disease, with long-term sequelae, often initiated early in life. Managing caries and carious lesions often has long-term consequences. These consequences involve the health (or its absence) generated by a caries management strategy, but also costs. This article discusses the long-term health and costs consequences resulting from different caries management strategies. It is demonstrated why, and under which circumstances, minimal invasive caries management may be beneficial for patients, but also for health services, with regard to both health gained and costs generated. Moreover, possible factors influencing the cost-effectiveness of different caries management strategies will be discussed.

Key points

  • Caries management is a long-term exercise, and comprehensive and applicable health economic analyses on caries management strategies should accordingly attempt to use a long-term perspective.

  • A range of factors, such as an individual’s caries risk, the tooth or lesion to be treated, the setting and the study methodology, affect the outcomes of health economic studies.

  • Researchers should record data on costs in their studies. Patients and dentists should be aware of the interplay between effectiveness and costs.

  • Health economic analyses are useful to support decision making in health services organization and commissioning.

  • Minimal invasive caries management is often, but not always, more effective, but also less costly, especially in the long term.


Dental caries is a chronic, behaviorally determined, and bacterially associated disease. Considering that teeth are present from early life onward, and especially in a patient with risky behavior (frequent carbohydrate consumption, poor oral hygiene, limited supply of topical fluorides), teeth are at risk of developing carious lesions from early in their life, with long-term sequelae. Any management strategy for dental caries has both initial and long-term consequences; these involve the preservation or generation of health (or the occurrence of adverse events) as well as the costs generated. This article discusses the long-term health and costs consequences resulting from different caries management strategies.

Health and costs are associated

Most caries management strategies are not a permanent “fix” for dental caries, because it will require repetition or some kind of re-treatment in the future. For example, the preventive application of fluoride varnish usually requires repetition, and not all lesions will be prevented; hence, even surfaces that had received a fluoride varnish some years previously may develop a carious lesion, and this lesion could progress to a status where a restoration is needed. Also, a restoration seldom lasts a lifetime, but rather fails after a statistically defined period—which may be 5 or 25 years depending on the restoration material, the operator, and, first and foremost, the patient. Similarly, a re-intervention on a restoration may involve a repair or a replacement, again with chances that further treatments may be needed. The cycle of long-term interventions resulting from dental caries has been termed the “cycle of re-interventions,” “restorative cycle,” or “death spiral of restorations,” with all terms emphasizing that restorative interventions are not unlimitedly repeatable: each re-restoration is larger than the previous one and, at some stage, dentists may run out of restorative options, requiring the tooth to be removed ( Fig. 1 ). In short, caries management is a lifetime story.

Fig. 1
Spiral of re-interventions, also termed “death spiral of the tooth” or “restorative cycle.”
( Data from Qvist V. Longevity of restorations: the ‘death spiral’. In: Fejerskov O, Kidd EAM, eds. Dental Caries: The Disease and Its Clinical Management. Vol 2. Oxford: Blackwell Munksgaard; 2008:444-455; and Brantley C, Bader J, Shugars D, Nesbit S. Does the cycle of rerestoration lead to larger restorations? The Journal of the American Dental Association. 1995;126(10):1407-1413.)

Any caries management strategy will thus either preserve health (eg, avoiding the occurrence of carious lesions), regain health (by restoring cavities and tooth functionality or esthetics), or lose health (if a treatment fails, for example if the pulp is exposed in a carious tooth during operative interventions). Regardless of this health gain or loss, each procedure incurs costs. However, not only the initial caries management, but also the described re-treatment of caries and carious lesions generates costs. These costs may be lower, as high as, or often even higher than the initial costs; the latter mainly because re-treatments will often be more extensive and complex (eg, repeated re-restoration of a tooth, for example, may eventually involve crowns; tooth removal of teeth that are nonrestorable may lead to the need for a fixed or removable dental prosthesis placement or an implant-supported single crown). Hence, the initial health gains provided by an intervention will be linked to the long-term costs; saving money early on might be less relevant than being effective long term, as this may reduce long-term costs.

In summary, caries management has long-term health and costs implications. The long-term consequences of any kind of management (be it minimally invasive or not) need a long-term perspective.

Methods for assessing health and cost consequences in the long term

To assess the health and cost consequences of health care in the long term, health economic analyses are usually required. Health economics distinguishes between 4 different types of analyses; these are categorized according to the measured health outcome :

  • Cost-cost studies. In these analyses, no health benefit is assessed, but only the costs of interventions, assuming that their effectiveness is the same (this, however, is seldom the case). The costs considered by such analyses (and generally, all health economic analyses) differ according to the perspective of the study: sometimes, only costs covered by the patient or the health care system are included, while many studies aim to consider the wider (so-called societal) costs. A range of costs can be discriminated: (1) direct medical costs (for example for diagnostics and treatment, staff, materials, drugs), (2) direct nonmedical costs (for example for patient’s traveling to and from the dentist, for transportation costs between the laboratory and the dentists), (3) indirect costs (those for lost opportunities, as explained below), and (4) intangible costs (which cannot easily be quantified, eg, for stress or pain during treatment or side-effects of a medication). Indirect (often called opportunity) costs are costs generated by spending time on medical treatment (eg, attending a dentist) instead of laboring or leisuring (so-called absenteeism, ie, being absent from work), or being of lower productivity at work or enjoying leisure time to a lesser degree because of a disease (so-called presenteeism, because one is present but not fully “there”). Absenteeism includes the assessment of traveling, waiting, and treatment times, and so-forth. Absenteeism and presenteeism times can be multiplied with a value assigned to this time (assigning these values, however, is not easy, and may be highly dependent on the individual’s occupational status, or the value an individual places on his/her leisure time), resulting in a monetary value. Although cost-cost studies are rare, the described considerations around costs are relevant for all health economic analyses.

  • Cost-effectiveness studies. These assess the effectiveness of a treatment (with effectiveness being defined as a clinically measurable outcome, such as avoided DMFT [decayed, missing, and filled teeth] increment), and weigh this effectiveness against the costs. One main outcome parameter of these studies is the incremental cost-effectiveness ratio (ICER), which is the cost-difference of 2 interventions divided by the effectiveness difference. The ICER is usually a positive value and indicates the additional money a decision maker needs to spend to buy an increment of better health, assuming that the better treatment is more expensive, which is often the case. Sometimes, however, a more expensive treatment is less effective, or a less expensive one is also more effective; in these cases, the ICER is negative, indicating that there is no decision problem.

  • Cost-utility studies. These investigate the utility of a treatment, which is oftentimes measured as quality-adjusted or disability-adjusted life years. To elicit the subjective value individuals place on certain health states (like a retained tooth or an untreated carious lesion causing pain), many tools, often questionnaires, are used. Notably, the elicited values differ between settings, but also change over time, and have not been estimated for all dental health states (it is also highly complex to measure the utility value placed on 1 specific tooth and not the whole dentition). As long as utility values of different health states and organs/organ functions are elicited using the same or very similar tools (questionnaires), this also allows to compare interventions across different medical disciplines. Such analyses are useful for resource allocation.

  • Cost-benefit studies. These transform effectiveness or utility, that is the health outcome, into a monetary value. This again means that interventions for various diseases and across disciplines (dentistry, rheumatology, ophthalmology) can be measured on the same scale. More importantly, health gains and costs are also identically scaled, and interpreting the health gain by money spent is easier (interpreting the effectiveness gain, such as a prevented carious lesions, per money spent is less straightforward). These analyses have only been sparsely applied in dentistry so far.

Measuring health gains and costs and the resulting cost-effectiveness/utility/benefit can be performed in 2 ways:

  • The first involves collecting original data for the purpose of health economic analyses, for example, as part of a clinical (interventional or observational) study. Such data collection allows recording in detail the direct medical costs (staff hours, medical equipment used, materials consumed), direct nonmedical costs (transport costs, for example, for visiting the dental office) and indirect ones (recording traveling, waiting, and treatment times, for example). Moreover, the cost estimation and the effectiveness data collection are performed in the same setting. Alternative methods for measuring health and costs often need to use and combine data from different sources and settings (eg, university clinics, practices, even countries), as discussed below.

  • The second uses mathematical models. These are built on data not necessarily collected for the purpose of a health economic evaluation, for example, on meta-analyses of various effectiveness trials, or cost estimates yielded from other studies. These data are then used to populate the model. The mathematical models used are designed to follow individuals or teeth over a defined period of time (in line with the remarks above, ideally long term, to capture the long-term cost and effectiveness consequences). Individuals or teeth “start” the modeling period in a certain health state (for example a sound surface, which is either sealed or not sealed) and can move from there to another health state (eg, to an early carious lesion) or remain in the initial health state. If they moved to the next health state, they again have the option to move further forward (to a cavitated carious lesion, for example). Modeling studies hence allow longer sequences of events (eg, sealed sound tooth → lost sealant and carious surface → restoration →replaced restoration → extracted tooth → implant). The probability of each transition between health states is based on underlying data, and each transition comes with health losses or gains, and costs (for treatment, or indirect costs for presenteeism or absenteeism, for example). Modeling has the advantage of (1) being able to consider wider evidence than a single study (using data from a meta-analysis may be more robust than data from a single study); (2) extrapolate early events long term, something which is limited in most clinical studies (clinical studies are seldom able to follow individuals over a lifetime), (3) compare a large range of options for their costs and effectiveness (clinical studies will only compare few interventions against each other due resource constrains). However, modeling studies require a number of assumptions to be made, both in the construction of the model as well as the parameters used for modeling: they are subject to a range of uncertainties (the same, however, is true for clinical studies, where external and internal validity are limited to some degree and parameters are uncertain, too, as indicated for example by confidence intervals around any effectiveness estimates). The relevance of uncertainty is discussed next.

Uncertainty in health economics

Different uncertainties are discriminated in health economics : (1) structural uncertainty in the case of modeling studies (the structure of the model may affect the study outcome and should be varied to gauge the impact of the model structure on study findings); (2) heterogeneity (interventions in patients with different age or risk or profile, anterior or posterior teeth, proximal and occlusal surfaces all come with a possible different cost and effectiveness profile); and (3) parameter uncertainty (any parameter, be it the effectiveness estimate of a single study or a meta-analysis, as well as most cost input parameters, are not 100% certain).

All these uncertainties can be evaluated, for example, using univariate sensitivity analyses. Such analyses may vary an aspect of the study, for example, a structural component of the model, a patient’s caries risk profile, or an input parameter (such as the costs for the application of a fluoride varnish by a dental nurse instead of a dentist) to explore the importance of the uncertainty for the study findings. Obviously, modeling studies allow variation of a far greater number of parameters than clinical studies (clinical studies need to include different subgroups, for example, to evaluate the relevance of heterogeneity). Alternatively, modeling studies may vary all uncertain parameters jointly, which allows to quantify the overall uncertainty of a study outcome.

Uncertainty analyses are most relevant to inform decision makers. Consider, for example, a study comparing the costs and effectiveness of different interventions. If the ranking of interventions remains unchanged despite large uncertainty, this uncertainty may be acceptable for decision makers. In contrast, if an only small uncertainty in a study will nevertheless reverse the ranking of interventions, decision makers may not make a decision based on information gained by this study as it is too ambiguous.

The cost-effectiveness of minimal invasive caries management

In the following sections, the cost-effectiveness of different caries management strategies is discussed. First, caries prevention using fluoride varnish in children is discussed. Subsequently, the cost-effectiveness of different carious tissue removal strategies, as well as the Hall Technique, are presented. Finally, the cost-effectiveness of restoration renewal versus repair for partially defective restorations is discussed.

Cost-Effectiveness of Caries Prevention Using Fluoride Varnish

Professionally applied fluoride varnishes are known to be effective to reduce caries increment. However, varnish application generates costs (for the material and the staff who apply it, but also indirect costs as described above for patients attending the dentist). These initial costs for the application of the varnish may be compensated long term, if caries increment and the subsequent need for (relatively expensive) re-treatments (mainly restorations) can be avoided. There is a larger number of studies assessing the cost-effectiveness of fluoride varnish application; most of them, however, did not take a long-term perspective. A recent study used a simulation model to follow teeth which received in-office application of fluoride varnish versus those which did not over the lifetime of initially 12-year-old individuals. The study took a mixed public-private-payer perspective in Germany, where most of the population is covered by (statutory) public insurance, which covers nearly all (except very advanced or prosthetic) treatments. Treatments which are not covered are paid privately or by an additional private insurer (hence mixed perspective). To assess the impact of different caries risk, 3 risk groups (low, medium, and high risk) were additionally discriminated during modeling. A biannual application of fluoride varnish until age 18 was compared with no fluoride application. The effectiveness of the varnish application was derived from systematic reviews. The health outcome was caries increment (DMFT). Cost calculations were based on the fees German dentists would claim from the insurance and/or the individual; these fees are fixed and recorded in fee item catalogs. Future costs and effectiveness were discounted at 3% per annum. Discounting accounts for the fact that individuals value opportunities lost (money spent, health lost) or gained (money saved, health gained) now more highly than opportunities lost or gained in the future.

Initially, the individual was assumed to have 28 sound teeth. Depending on his or her caries risk, teeth had a certain probability of carious lesion development. This risk was modified (decreased) when fluoride varnish was assumed to be applied. If a carious lesion occurred (ie, caries increment), this was assumed to result in the placement of an adhesive composite restoration. If this restoration failed, re-restoration using another composite or further restorative strategies was modeled. Also, endodontic complications (leading to nonsurgical primary or secondary root-canal treatment or surgical re-treatment, ie, apicectomy, or extraction) were considered. If teeth needed extraction, tooth replacement via implant-supported crowns was simulated. Implants and implant-supported crowns were assumed to be prone to restorative complications (requiring re-cementation or renewal of crowns) as well as biologic (eg, peri-implantitis with subsequent implant loss) or technical complications (like abutment or implant fracture) according to a range of data sources. In short, the model aimed to simulate the whole restorative spiral shown in Fig. 1 .

The initial costs for the varnish were assumed to range between 12 and 14 Euro per application. Over the patients’ lifetime and as a mean of all risk groups, not applying fluoride during age 12 to 18 was the least costly (230 Euro), but also the least effective, strategy (mean caries increment was 11 DMFT). Applying the varnish was more costly, but also more effective (357 Euro, DMFT 7). The ICER was 39 Euro per avoided DMFT when the varnish was applied. The so-called cost-effectiveness plane is shown in Fig. 2 .

Jan 7, 2020 | Posted by in General Dentistry | Comments Off on Less Is More? The Long-Term Health and Cost Consequences Resulting from Minimal Invasive Caries Management

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