Investigational New Drugs19: 171–177, 2001.© 2001Kluwer Academic Publishers. Printed in the Netherlands.

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Body surface area as a determinant of pharmacokinetics and drug dosing

Michael Sawyer and Mark J. RatainCommittee on Clinical Pharmacology, Department of Medicine, and Cancer Research Center, The University ofChicago, Chicago, IL, USA

Key words:body surface area, dosage, phase I

Summary

Body surface area (BSA) was introduced into medical oncology in order to derive a safe starting dose for phaseI studies of anticancer drugs from preclinical animal toxicology data. It is not clear however, as to why dosingby BSA was extended to the routine dosing of antineoplastic agents. Several formulas exist to estimate BSA, butthe formula derived by DuBois and DuBois is the one used in adult medical oncology. This formula was derivedbased on data from only nine patients; subsequent attempts to validate the formula have found the DuBois formulato either over or underestimate the actual determined BSA. While cardiac output does correlate with BSA, therelationship between BSA and other physiologic measures relevant for drug metabolism and disposition, such as,renal and hepatic function, is weak or nonexistent. Further only epirubicin, etoposide, and carboplatin have beenstudied to determine if dosing by BSA would reduce interpatient variability, and none of these drugs were found tohave significant relationships between their pharmacokinetics and BSA. Future clinical trials of new agents shouldnot presume that dosing based on BSA reduces interpatient variability. Studies should examine the role, if any,BSA has in dosing new chemotherapeutic agents in initial phase I studies.

Introduction of BSA into medical oncology

Dosing by body surface (BSA) was introduced intooncology practice as a method of predicting a safestarting dose for phase I human trials from preclin-ical animal toxicology data. Pinkel first suggestedthat the maximum tolerated dose (MTD) expressedas mg/m2 was similar in different species. He reviewedthe MTD determined in animal and human studiesof mechlorethamine, methotrexate, 6-mercaptopurine,actinomycin D and triethylenethiophosphoramide(thi-otepa) and found that the MTDs to be similar whenexpressed as mg/m2 [1]. Freireich and colleagues ex-amined 18 chemotherapeutic agents and compared theactual human MTD to that predicted from preclinicalanimal studies [2] and concluded that the animal dataaccurately predicted the human MTD. While theseauthors proposed dose normalization to estimate theinitial phase I starting dose, neither paper commentedon the utility of using BSA dosing in dose escalationschemes. Indeed, it remains an enigma as to why sub-

sequent phase I studies extended the use of BSA frompredicting the initial starting dose, to its incorporationas a dosing parameter for all adult patients.

BSA formulas

Several formulas for calculating the BSA from a pa-tient’s height and weight have been proposed but themethod determined by DuBois and DuBois has pre-vailed. These authors studied 9 individuals ranging inweight from 25 to 90 kg. Subjects had a mold madeof their body, and the mold was cut into small piecesthat would lay flat; the pieces were then photographedand the surface area was calculated. From these 9 sub-jects, DuBois and DuBois determined by iteration thatBSA was related to height and weight by the formula.007184× weight0.425 × height0.725. As the studyincluded only one child and no adolescents, the applic-ation of the DuBois formula to pediatric populationsor adults outside the weight range in the original study

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is of uncertain accuracy. Furthermore, the child in thestudy was severely malnourished, weighing only 6.3kg at the age of 21 months [3].

Recently, several papers have indeed questionedthe accuracy of the DuBois formula [4,5]. Mitchell etal. examined the formula’s accuracy in predicting theBSA of 237 males with BSAs ranging from 1.3 m2

to 2.1 m2. Each subject’s true BSA was determinedby photometric measurement in contrast to the methodused by DuBois, which involved the making of plasterof Paris models. While there was a strong correla-tion (r = 0.97) between BSA predicted by the DuBoisformula and the photometric measurement of BSA,but they noted that the DuBois formula consistentlyunderestimated body surface area, an error which be-came larger at smaller surface areas [4]. Gehan andGeorge reported on the relationship between BSA andheight and weight in 401 individuals, in retrospectivefashion, obtaining morphometric data from a paperby Boyd published in 1936. Gehan and George de-rived the formula; BSA = 0.02350× Height0.422246

× Weight0.51456 which worked well in both childrenand adults. They further noted that the DuBois formulatended to overestimate the observed BSA [5]. Theyexamined the accuracy of the DuBois formula’s pre-dictions in their 401 subjects. They found the DuBoisformula overestimated by≥ 15% in 16.5% of subjects,and underestimated the surface area by≥15% in 1%.These two errors taken together imply that the DuBoisformula has a relative error of at least 15% in 17.5%of the patients in the Gehan and George study.

The failure of studies to validate the DuBois for-mula and the contradictory reports that it either over-estimates or underestimates body surface area raisequestions about the formula’s ability to accuratelyindividualize cancer chemotherapy doses by normal-ization to body surface area.

Body surface area and hepatic function

In the 1950’s, body surface area was introduced intogeneral pharmacology and the dosing of medicationsbased on the belief that physiologic parameters relev-ant to drug metabolism and elimination, such as thebasal metabolic rate, renal and hepatic function andcardiac output, scaled between individuals accordingto surface area [6]. This fundamental belief is thebasis for normalizing drug kinetics and dosing to bodysurface area. However, the fact that surface area hasever been used to normalize the basal metabolic rate

in animals of different size is a fallacy. Review ofthe original papers shows that the basal metabolic rateis normalized when expressed in terms of weight topower 0.75, not to weight to the power 0.425 which isthe weight term found in the DuBois formula [7].

The assumption that basal metabolic rate is scaledto body surface area has led to investigators attempt-ing to normalize renal, hepatic and other physiologicfunctions to body surface area. There is weak evid-ence that surface area correlates with any measure oforgan function. The one exception may be cardiac out-put, which does normalize to a narrow range whenexpressed in terms of body area.

The clearance of drugs metabolized by the liverhas not been correlated with BSA. These studies,which have shown the failure of BSA to decreaseinterpatient variability, however do show clearancecorrelated to lean body weight. Murry et al. studiedhepatic drug metabolism and correlated it with livervolume in 16 children. Each child had undergone adiagnostic abdominal MRI during the course of treat-ment and follow-up for malignancy, and the volumeof the liver was determined from these scans. Withinfour months of having the MRI, each child under-went pharmacokinetic studies of indocyanine green,lorazepam, and antipyrine. Liver volume was stronglycorrelated with age (r2 = 0.88), body weight (r2 =0.68), height (r2 = 0.80), and BSA (r2 = 0.76) and ifliver volume was expressed in terms of body weight, itdecreased with increasing age. Liver volume was cor-related with BSA, but did not decrease with increasingage. Clearance of lorazepam and ICG correlated withliver volume, but the clearance of antipyrine did notcorrelate with liver volume. The authors suggestedthat normalizing the clearance of antipyrine to BSAremoved the effect of age on the clearance of anti-pyrine. Examination of the author’s reported valuesof antipyrine clearance/m2, show that antipyrine clear-ance corrected to BSA varied widely from 500 to 900ml/m2 from age 3 to age 18 and the interpatient vari-ability did not decrease with normalization to BSA.This study’s results are difficult to generalize for sev-eral reasons; the children had hematological or solidtumor malignancies with abnormalities in liver en-zymes. The study did not discuss what medicationsthe children had received or were currently on, and ifthe patient’s MRIs revealed the presence of liver meta-stases. The only result of the study, which are certain,is the relationship between liver volume and patientdemographics [8].

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A more recent study by Nawaratne et al. used CTscans to determine the liver and kidney volume in 23adult patients who were free of cancer and had normalliver and renal function. The authors found strong cor-relations with liver volume and total body weight (r2 =0.61), followed by BSA (r2 = 0.54) and only a modestcorrelation with lean body weight (LBW) (r2 = 0.21).Despite the poor correlation with liver volume, LBWwas the only variable to be significantly correlated (r2

= 0.43) with antipyrine clearance; BSA was not sig-nificantly correlated with antipyrine clearance despiteits strong correlation with liver volume [9]. Other stud-ies have shown weak correlations between antipyrineclearance and liver volume (r2 = 0.29 to 0.48) [9–13] and given the strong correlation between BSA andliver volume (r2 = 0.54 to 0.76) [8,9] it is unlikely thatclinically relevant relationships will be found betweenliver oxidative metabolism of drugs and BSA.

Body surface area and renal function

Some evidence exists for BSA correlating with renalfunction, but many of the classic references concern-ing BSA and renal function used urea clearance andnot creatinine clearance as an index of renal func-tion [14–16]. This may appear a minor point, buturea clearance more accurately measures renal tubularfunction than glomerular filtration rate, which is betterdetermined by creatinine clearance.

McIntosh et al. were among the first to study therelationship between renal function and BSA. Theystudied 8 children ranging in age from 3 to 13 yearsold. In the study, renal function was evaluated us-ing urea clearance and not creatinine clearance. Theyfound that urea clearance was correlated with BSA andthat urea clearance expressed in terms of surface areagave the same values in children and adults [16].

Holten was the first investigator to examine therelationship between creatinine clearance and bodysurface area. He studied 90 children ranging from9 months to 17 years, the majority of whom wererecovering from mild diphtheria and did not have al-buminuria. He noted creatinine clearance correlatedwith increasing surface area. He did not quantify thestrength of the relationship probably due to the lack ofstatistical tools available to him in 1932 [17]. Usingmore modern techniques and statistics, Nawaratne etal. examined the relationship of renal function to kid-ney and body size. Kidney volume was related to totalbody weight (r2 = 0.24), BSA (r2 = 0.43) but more

strongly related to lean body weight (r2 = 0.49). Inmultiple regression analysis, creatinine clearance var-ied with only age and kidney volume but in univariantanalysis lean body weight was significantly correlatedwith renal function (r2 = 0.35, p = 0.005). The lackof a significant relationship between LBW and renalfunction in the multivariate analysis is not surprisinggiven the strong correlation between kidney volumeand LBW. No significant correlation between BSA andcreatinine clearance was found in either univariant ormultivariate analysis [9].

Peters studied 41 patient’s glomerular filtrationrate using technetium 99m DTPA (diethylenetriaminepentaacetic acid) and used statistical moment theory todetermine the ratio of glomerular filtration rate (GFR)to extracellular fluid volume (ECF). The usual prac-tice of normalizing GFR to BSA gives two differentnormal ranges, one for men and one for women [18].He found that normalizing GFR to extracellular fluideliminated the gender differences in GFR.

A study by Martin et al. raises the most doubt aboutthe utility of body surface as a significant variableto predict creatinine clearance. In this recent study,Martin et al. examined the accuracy and precisionof the Cockcroft-Gault formula in predicting creatin-ine clearance in cancer patients. They determined theglomerular filtration rate using 51Cr-EDTA (ethylene-diamine tetraacetic acid) in 123 cancer patients, 55of who had been treated with cisplatin. The authorsperformed a NONMEM analysis on the data set fromeighty patients to derive a formula to predict GFR, andthen validated the formula with the remaining 43 pa-tients. In the NONMEM analysis the most significantmorphological variable was actual body weight andnot body surface area and the formula that gave thebest prediction was based on actual body weight, age,sex and serum creatinine [19].

Body surface area and volume of distribution

In physiology, BSA is related to the volumes of vari-ous compartments such as extracellular and plasmavolume but lean body mass is more predictive of thesevolumes than BSA. Early investigators showed thatblood volume was related to body surface area [20].In 1969, Retzlaff et al. confirmed the earlier stud-ies showing a relationship between BSA and bloodvolume. In their study actual body weight was not asaccurate as BSA in normalizing blood volume, butBSA was inferior to lean body weight in normaliz-

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ing blood volume. Boer studied 87 healthy individualsto determine the relationship between different bodyfluid volumes and individual measurements. In thisstudy, lean body weight had the strongest relationshipto plasma volume, blood volume, extracellular volumeand intracellular volume. BSA or formulas based onheight and weight are related to physiologic volumes,but the strength of the relationship to BSA is not asstrong as the relationship between lean body weightand these physiologic volumes [21]. These studiessuggest that the best morphometric measurement topredict physiologic volumes is lean body weight andnot body surface area.

The application of the relationships of either BSAor LBW to predict drug concentrations must betempered by the extensive protein binding of mostcancer chemotherapeutic drugs. This binding will bealtered by levels of proteins such as albumin and al-pha 1 glycoprotein and by displacement of proteins byother drugs. A paper by Bruno et al., which looked atthe population pharmacokinetics of docetaxel, foundthat the levels of alpha 1 acidglycoprotein were a ma-jor determinant of the pharmacokinetics of docetaxel[22].

Body surface area and cardiac output

Cardiac output was one of the first physiologic para-meters examined for a relationship to BSA. Burwelland Robinson studied 11 patients and observed thatcardiac output expressed in terms of body surface areanormalized cardiac output, with a range from 1.9 to2.5 l/min/m2. Grollman in a later study confirmed theearlier findings of Burwell and Robinson. He stud-ied 51 medical students and found that cardiac outputnormalized to BSA, had a mean value of 2.2 witha standard deviation of 0.3 l/min/m2. De Simone etal. in 1997 examined the cardiac output and strokevolume in 970 children and adults with echocardio-graphy. They studied a more diverse population withages ranging from 1 day old to 85 years old, and204 were overweight which is in contrast to the studypopulation in the original BSA and cardiac outputarticle. De Simone showed that BSA was related tostroke volume and cardiac output, cardiac output andstroke volume were related to body weight raised tothe power 0.71 [23].

The fundamental physiologic processes that formthe basis for drug metabolism and disposition havemodest or weak correlations with body surface area.

Even where modest correlations do exist betweensurface area and drug eliminating or metabolizing pro-cess, the relationship is not as strong as with othermeasures such as lean body weight or total bodyweight. The weakness of body surface area is moreobvious when the kinetics of individual drugs areexamined for a relationship with body surface area.

Body surface area and individual drugs

Therapeutic drug monitoring has been advanced asa method to diminish toxicity and improve responserates in cancer treatment. This approach to improveresponse rates has been hampered by weak relation-ships between kinetics and tumor response. Numerousinvestigators have shown relationships between tox-icity and drug pharmacokinetics such as area under theconcentration time curve or concentrations at steadystate [24–26]. Generally pharmacokinetic parametersare better predictors of toxicity than surface area. Theonly drug for which BSA has been found to have asignificant correlation with clearance is docetaxel al-though height was related to clearance of paclitaxel inone study.

Bruno et al. constructed a population model of do-cetaxel from the pharmacokinetic data obtained from22 phase II trial. Using NONMEM they developed amodel to predict docetaxel clearance in which the sig-nificant covariates alpha1 acid-glycoprotein, hepaticfunction, age body surface area and albumin [22].

Grochow and colleagues reviewed the pharma-cokinetics of 9 chemotherapy drugs examined in16 phase II trials. They examined the relationshipbetween drug clearance, the volume of the centralcompartment, and the volume at steady state withpatients’ height, weight and BSA. Paclitaxel wasthe only agent that had a significant relationshipbetween its clearance and a morphometric measure-ment, height. Of the 96 relationships examined, only 5relationships were found to exist between a drug phar-macokinetics and morphometric measurements [27].

The relationship between BSA and dosing for car-boplatin and epirubicin has been studied extensively.In the case of both drugs, dosing by BSA was foundnot to be the best method to predict the dose for apatient Cosolo and colleagues were the first to ques-tion the rationale of adjusting the dose of epirubicinusing a patient’s body surface area. They studied thepharmacokinetics of epirubicin in10 patients receivingsingle agent epirubicin and attempted to correlate pa-

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tient characteristics with epirubicin’s pharmacokineticparameters. They found a wide variation in epirubicinclearance ranging from 500 to 2000 ml/min, whichwas correlated with lean body weight (r = 0.65), butepirubicin clearance was not related to BSA or totalbody weight [28]. Dobbs and Twelves studied epi-rubicin clearance in 32 men and women receivingepirubicin chemotherapy and found epirubicin clear-ance was not correlated with BSA [29]. Gurney et al.administered an unadjusted dose of epirubicin 150 mgto 20 chemotherapy naïve patients. They did not finda significant relationship between any of epirubicin’spharmacokinetic parameters and BSA, however theydid find epirubicin’s pharmacokinetics were relatedto numerous measures of liver function. Epirubicin’sAUC was correlated with the prothrombin index (p< 0.01), antipyrine clearance (p < 0.05) and bilesalt concentration (p = 0.03) [30]. These studies raisemajor questions regarding the utility of BSA to indi-vidualize the dosage of epirubicin.

When carboplatin was first introduced, the dose ofcarboplatin was based on surface area, but medical on-cologists quickly realized that many patients were un-derdosed while others experienced significant toxicity[31]. Several investigators examined carboplatin dos-ing based on measures of renal function. Carboplatinis primarily eliminated by glomerular filtration andits non-renal elimination is only 25 ml/min [32,33].Egorin et al. were the first to derive and validate anequation to dose carboplatin based on BSA, prior treat-ment and glomerular filtration rate, this equation wasbased on the relationship between carboplatin AUCand the platelet nadir [34]. Calvert validated the prin-ciple of dosing carboplatin based on renal function andderived a simpler formula to dose carboplatin. Calvertet al. studied 18 patients, with a measured glomerularfiltration rate ranging from 33 to 136 ml/min, whowere treated with carboplatin. They found a strongrelationship between carboplatin clearance and GFR,(r = .85), and derived the formula dose carboplatin= AUC×(GFR+25). They prospectively validated thisformula in an additional 31 patients. They did notfind a significant relationship between the nonrenalclearance and body surface area [35].

Piotrovsky et al. recently analyzed the all phar-macokinetic obtained from studies of vorozole usingNONMEM. This data set comprised drug levels froma frequent sampling strategy from 84 healthy menand women and 13 women with breast cancer anddata from a limited sampling strategy comprising 286breast cancer patients. They did not find vorozole cor-

relating with any demographic variable such as totalbody weight, body surface area or lean body mass.The volume of distribution did correlate with weightbut was not correlated with body surface area [36].

Etoposide’s pharmacokinetics were studied byRatain and colleagues at the University of Chicago,during studies of adaptive dosing of etoposide infu-sions. They found substantial interpatient variabilityof etoposide clearance with a coefficient of variation of30 percent. Expressing etoposide clearance in ml/minas opposed to ml/min/m2 did not significantly increaseinterpatient variability. There was no significant rela-tionship between surface area and etoposide clearance[37]. The lack of a relationship was confirmed by astudy by Nguyen et al., in which they examined thepharmacokinetics of etoposide in 100 patients. In these100 patients, they obtained 1044 etoposide concentra-tions and performed an analysis on this data set usingNONMEM. They did find a relationship between bodysurface area and volume of distribution, but normaliz-ation of the volume of distribution decreased the coef-ficient of variation from 57% to only 34%. Etoposideclearance was related to albumin, serum protein, totalbody weight, serum creatinine and the presence or ab-sence of liver metastasis, but body surface area wasnot a significant determinant of clearance [38].

Gurney, in a recent review of body surface area,advocated abandoning body surface area and dosingchemotherapy based on the prime dose, modifying thedose for known covariates of metabolism, and adjust-ing dose for toxicity. He advocates that for each druga prime fixed dose be determined for each drug. Thisprime dose would be modified rationally on known co-variates of drug clearance such as glomerular filtrationrate, elevation of liver enzymes or bilirubin. In con-trast to most authors he advocates adjusting the dose ofchemotherapy upward in the absence of toxicity [39].

Conclusion

BSA was introduced in medical oncology to safelypredict a suitable starting dose in phase I clinical tri-als from preclinical animal toxicology data. From thatstarting point in phase I trials it has spread throughoutthe practice of oncology with little justification. Theformula to calculate body surface area takes two pre-cisely quantifiable variables, height and weight, andestimates a value for surface area. The formula usedto do this has never been adequately validated. Veryfew of the organ functions that determine the phar-

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macokinetics of a drug are related to body surfacearea; further when organ function has been related tobody surface area other measures such as lean bodyweight have been found superior to surface area. Forthe majority of drugs, the relationship between BSAand kinetics has not been studied and where the rela-tionship between BSA and kinetics has been examinedonly a few drugs such as the taxanes have relationshipsbeen found. Even the work done by Bruno et al. ondocetaxel, which is usually cited as supporting the useof surface area to dose chemotherapy, has an alternat-ive interpretation. In their paper they only used BSAin their final model and did not use weight, becausethe common practice in oncology was to use surfacearea. A more rational approach is to not assume at theoutset in the development of a drug that body surfaceis a significant determinant in the pharmacokineticsor pharmacodynamics of a drug. Instead the initialstudies should employ fixed dosing and surface areashould be examined like all other covariates such asGFR, liver function tests, albumin and age.

Acknowledgments

M. Sawyer is the Gordon E. Richards Fellow of theCanadian Cancer Society, Ontario Division.

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Address for offprints:Mark J. Ratain, University of Chicago, 5841S Maryland Ave., MC 2115 Chicago, IL 60637-1470, USA